Filter bubble - Knowledge

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when people are given the option to click on a link offering contrasting views, they still default to their most viewed sources. "ser choice decreases the likelihood of clicking on a cross-cutting link by 17 percent for conservatives and 6 percent for liberals." A cross-cutting link is one that introduces a different point of view than the user's presumed point of view or what the website has pegged as the user's beliefs. A recent study from Levi Boxell, Matthew Gentzkow, and Jesse M. Shapiro suggest that online media isn't the driving force for political polarization. The paper argues that polarization has been driven by the demographic groups that spend the least time online. The greatest ideological divide is experienced amongst Americans older than 75, while only 20% reported using social media as of 2012. In contrast, 80% of Americans aged 18–39 reported using social media as of 2012. The data suggests that the younger demographic isn't any more polarized in 2012 than it had been when online media barely existed in 1996. The study highlights differences between age groups and how news consumption remains polarized as people seek information that appeals to their preconceptions. Older Americans usually remain stagnant in their political views as traditional media outlets continue to be a primary source of news, while online media is the leading source for the younger demographic. Although algorithms and filter bubbles weaken content diversity, this study reveals that political polarization trends are primarily driven by pre-existing views and failure to recognize outside sources. A 2020 study from Germany utilized the Big Five Psychology model to test the effects of individual personality, demographics, and ideologies on user news consumption. Basing their study on the notion that the number of news sources that users consume impacts their likelihood to be caught in a filter bubble—with higher media diversity lessening the chances—their results suggest that certain demographics (higher age and male) along with certain personality traits (high openness) correlate positively with a number of news sources consumed by individuals. The study also found a negative ideological association between media diversity and the degree to which users align with right-wing authoritarianism. Beyond offering different individual user factors that may influence the role of user choice, this study also raises questions and associations between the likelihood of users being caught in filter bubbles and user voting behavior.

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reported research and perspectives on the roles filter bubbles play in regards to health misinformation. Drawing from various fields such as journalism, law, medicine, and health psychology, the book addresses different controversial health beliefs (e.g. alternative medicine and pseudoscience) as well as potential remedies to the negative effects of filter bubbles and echo chambers on different topics in health discourse. A 2016 study on the potential effects of filter bubbles on search engine results related to suicide found that algorithms play an important role in whether or not helplines and similar search results are displayed to users and discussed the implications their research may have for health policies. Another 2016 study from the Croatian Medical journal proposed some strategies for mitigating the potentially harmful effects of filter bubbles on health information, such as: informing the public more about filter bubbles and their associated effects, users choosing to try alternative search engines, and more explanation of the processes search engines use to determine their displayed results.

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voted for Obama or Romney in the 2012 presidential election. They then identified whether news stories were read after accessing the publisher's site directly, via the Google News aggregation service, web searches, or social media. The researchers found that while web searches and social media do contribute to ideological segregation, the vast majority of online news consumption consisted of users directly visiting left- or right-leaning mainstream news sites and consequently being exposed almost exclusively to views from a single side of the political spectrum. Limitations of the study included selection issues such as Internet Explorer users skewing higher in age than the general internet population; Bing Toolbar usage and the voluntary (or unknowing) sharing of browsing history selection for users who are less concerned about privacy; the assumption that all stories in left-leaning publications are left-leaning, and the same for right-leaning; and the possibility that users who are

115: 532:—the largest social media platform in China—to examine the structure of filter bubbles regarding to their effects on polarization. The study draws a distinction between two conceptions of polarization. One being where people with similar views form groups, share similar opinions, and block themselves from differing viewpoints (opinion polarization), and the other being where people do not access diverse content and sources of information (information polarization). By utilizing social bots instead of human volunteers and focusing more on information polarization rather than opinion-based, the researchers concluded that there are two essential elements of a filter bubble: a large concentration of users around a single topic and a uni-directional, star-like structure that impacts key information flows. 429:

suggested that the effects attributed to them may stem more from preexisting ideological biases than from algorithms. Similar views can be found in other academic projects, which also address concerns with the definitions of filter bubbles and the relationships between ideological and technological factors associated with them. A critical review of filter bubbles suggested that "the filter bubble thesis often posits a special kind of political human who has opinions that are strong, but at the same time highly malleable" and that it is a "paradox that people have an active agency when they select content but are passive receivers once they are exposed to the algorithmically curated content recommended to them."

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mode, most people saw results unique to them. Google included certain links for some that it did not include for other participants, and the News and Videos infoboxes showed significant variation. Google publicly disputed these results saying that Search Engine Results Page (SERP) personalization is mostly a myth. Google Search Liaison, Danny Sullivan, stated that “Over the years, a myth has developed that Google Search personalizes so much that for the same query, different people might get significantly different results from each other. This isn’t the case. Results can differ, but usually for non-personalized reasons.”

774:'s harvesting and use of user data for at least 87 million Facebook profiles during the 2016 presidential election highlight the ethical implications of filter bubbles. Co-founder and whistleblower of Cambridge Analytica Christopher Wylie, detailed how the firm had the ability to develop "psychographic" profiles of those users and use the information to shape their voting behavior. Access to user data by third parties such as Cambridge Analytica can exasperate and amplify existing filter bubbles users have created, artificially increasing existing biases and further divide societies. 512: 155:, the top fifty Internet sites, from CNN to Yahoo to MSN, install an average of 64 data-laden cookies and personal tracking beacons. Search for a word like "depression" on Dictionary.com, and the site installs up to 223 tracking cookies and beacons on your computer so that other Web sites can target you with antidepressants. Share an article about cooking on ABC News, and you may be chased around the Web by ads for Teflon-coated pots. Open—even for an instant—a page listing signs that your spouse may be cheating and prepare to be haunted by DNA paternity-test ads. 798: 643:

aggregator apps scan all current news articles and direct you to different viewpoints regarding a certain topic. Users can also use a diversely-aware news balancer which visually shows the media consumer if they are leaning left or right when it comes to reading the news, indicating right-leaning with a bigger red bar or left-leaning with a bigger blue bar. A study evaluating this news balancer found "a small but noticeable change in reading behavior, toward more balanced exposure, among users seeing the feedback, as compared to a control group".

721:. Filter bubbles in popular social media and personalized search sites can determine the particular content seen by users, often without their direct consent or cognizance, due to the algorithms used to curate that content. Self-created content manifested from behavior patterns can lead to partial information blindness. Critics of the use of filter bubbles speculate that individuals may lose autonomy over their own social media experience and have their identities socially constructed as a result of the pervasiveness of filter bubbles. 29: 652:

highly talked-about events there. Facebook's strategy is to reverse the Related Articles feature that it had implemented in 2013, which would post related news stories after the user read a shared article. Now, the revamped strategy would flip this process and post articles from different perspectives on the same topic. Facebook is also attempting to go through a vetting process whereby only articles from reputable sources will be shown. Along with the founder of

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technology that automatically limits their exposure to information that would challenge their world view. Some researchers argue, however, that because users still play an active role in selectively curating their own newsfeeds and information sources through their interactions with search engines and social media networks, that they directly assist in the filtering process by AI-driven algorithms, thus effectively engaging in self-segregating filter bubbles.

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posted or re-posted by these "second-tier" friends. The study found that "24 percent of the news items liberals saw were conservative-leaning and 38 percent of the news conservatives saw was liberal-leaning." "Liberals tend to be connected to fewer friends who share information from the other side, compared with their conservative counterparts." This interplay has the ability to provide diverse information and sources that could moderate users' views.

453:" to test their hypothesis on the environments of Reddit and Twitter. The researchers gauged changes in polarization in regularized social media networks and non-regularized networks, specifically measuring the percent changes in polarization and disagreement on Reddit and Twitter. They found that polarization increased significantly at 400% in non-regularized networks, while polarization increased by 4% in regularized networks and disagreement by 5%. 783:

that makes it difficult for users to determine the source of the content, leading them to decide for themselves whether the source is reliable or fake. That can lead to people becoming used to hearing what they want to hear, which can cause them to react more radically when they see an opposing viewpoint. The filter bubble may cause the person to see any opposing viewpoints as incorrect and so could allow the media to force views onto consumers.

55:. The search results are based on information about the user, such as their location, past click-behavior, and search history. Consequently, users become separated from information that disagrees with their viewpoints, effectively isolating them in their own cultural or ideological bubbles, resulting in a limited and customized view of the world. The choices made by these algorithms are only sometimes transparent. Prime examples include 528:

between exposure to differing views, although it warned that the findings should be limited to party-registered American Twitter users. One of the main findings was that after exposure to differing views (provided by the bots), self-registered republicans became more conservative, whereas self-registered liberals showed less ideological change if none at all. A different study from The People's Republic of China utilized social bots on

984:, Retrieved October 10, 2017, "....A filter bubble is the intellectual isolation, that can occur when websites make use of algorithms to selectively assume the information a user would want to see, and then give information to the user according to this assumption ... A filter bubble, therefore, can cause users to get significantly less contact with contradicting viewpoints, causing the user to become intellectually isolated...." 732:, have expressed concerns regarding the risks of privacy and information polarization. The information of the users of personalized search engines and social media platforms is not private, though some people believe it should be. The concern over privacy has resulted in a debate as to whether or not it is moral for information technologists to take users' online activity and manipulate future exposure to related information. 348:" was overblown. Weisberg asked Google to comment, and a spokesperson stated that algorithms were in place to deliberately "limit personalization and promote variety." Book reviewer Paul Boutin did a similar experiment to Weisberg's among people with differing search histories and again found that the different searchers received nearly identical search results. Interviewing programmers at Google, off the record, journalist 230:, which happens when the internet becomes divided into sub-groups of like-minded people who become insulated within their own online community and fail to get exposure to different views. This concern dates back to the early days of the publicly accessible internet, with the term "cyberbalkanization" being coined in 1996. Other terms have been used to describe this phenomenon, including " 763:

increasingly discussed possibility is to design social media with more serendipity, that is, to proactively recommend content that lies outside one's filter bubble, including challenging political information and, eventually, to provide empowering filters and tools to users. A related concern is in fact how filter bubbles contribute to the proliferation of "

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together to filter out News Feeds. They also criticized Facebook's small sample size, which is about "9% of actual Facebook users," and the fact that the study results are "not reproducible" due to the fact that the study was conducted by "Facebook scientists" who had access to data that Facebook does not make available to outside researchers.

342:," and sending Weisberg screenshots of their results. The results varied only in minor respects from person to person, and any differences did not appear to be ideology-related, leading Weisberg to conclude that a filter bubble was not in effect, and to write that the idea that most internet users were "feeding at the trough of a 81:, according to Pariser, but contrasting views regard the effect as minimal and addressable. According to Pariser, users get less exposure to conflicting viewpoints and are isolated intellectually in their informational bubble. He related an example in which one user searched Google for "BP" and got investment news about 182:, Pariser warns that a potential downside to filtered searching is that it "closes us off to new ideas, subjects, and important information," and "creates the impression that our narrow self-interest is all that exists." In his view, filter bubbles are potentially harmful to both individuals and society. He criticized 684:

web browser, announced the formation of the Mozilla Information Trust Initiative (MITI). The +MITI would serve as a collective effort to develop products, research, and community-based solutions to combat the effects of filter bubbles and the proliferation of fake news. Mozilla's Open Innovation team

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of a search inquiry rather than the literal syntax of the question, Google is attempting to limit the size of filter bubbles. As of now, the initial phase of this training will be introduced in the second quarter of 2018. Questions that involve bias and/or controversial opinions will not be addressed

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When filter bubbles are in place, they can create specific moments that scientists call 'Whoa' moments. A 'Whoa' moment is when an article, ad, post, etc., appears on your computer that is in relation to a current action or current use of an object. Scientists discovered this term after a young woman

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creates opportunities for individuals to discuss political events with their peers, including those with whom they have weak social ties." According to these studies, social media may be diversifying information and opinions users come into contact with, though there is much speculation around filter

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for offering users "too much candy and not enough carrots." He warned that "invisible algorithmic editing of the web" may limit our exposure to new information and narrow our outlook. According to Pariser, the detrimental effects of filter bubbles include harm to the general society in the sense that

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and democratic processes, as well as the rise of "ideological media". These scholars fear that users will be unable to " beyond narrow self-interest" as filter bubbles create personalized social feeds, isolating them from diverse points of view and their surrounding communities. For this reason, an

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Similarly, Google, as of January 30, 2018, has also acknowledged the existence of a filter bubble difficulties within its platform. Because current Google searches pull algorithmically ranked results based upon "authoritativeness" and "relevancy" which show and hide certain search results, Google is

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In light of recent concerns about information filtering on social media, Facebook acknowledged the presence of filter bubbles and has taken strides toward removing them. In January 2017, Facebook removed personalization from its Trending Topics list in response to problems with some users not seeing

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Users can take many actions to burst through their filter bubbles, for example by making a conscious effort to evaluate what information they are exposing themselves to, and by thinking critically about whether they are engaging with a broad range of content. Users can consciously avoid news sources

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as defined by Robert Putman. Pariser argues that filter bubbles reinforce a sense of social homogeneity, which weakens ties between people with potentially diverging interests and viewpoints. In that sense, high bridging capital may promote social inclusion by increasing our exposure to a space that

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In June 2018, the platform DuckDuckGo conducted a research study on the Google Web Browser Platform. For this study, 87 adults in various locations around the continental United States googled three keywords at the exact same time: immigration, gun control, and vaccinations. Even in private browsing

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is, people are more likely to befriend/follow people who share similar beliefs. The nature of the algorithm is that it ranks stories based on a user's history, resulting in a reduction of the "politically cross-cutting content by 5 percent for conservatives and 8 percent for liberals." However, even

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addressed the lack of a clear and testable definition for filter bubbles across disciplines; this often results in researchers defining and studying filter bubbles in different ways. Subsequently, the study explained a lack of empirical data for the existence of filter bubbles across disciplines and

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The concept of a filter bubble has been extended into other areas, to describe societies that self-segregate according political views but also economic, social, and cultural situations. That bubbling results in a loss of the broader community and creates the sense that for example, children do not

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that's been catered by these algorithms." An internet user's past browsing and search history is built up over time when they indicate interest in topics by "clicking links, viewing friends, putting movies in queue, reading news stories," and so forth. An internet firm then uses this information to

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Filter bubbles have stemmed from a surge in media personalization, which can trap users. The use of AI to personalize offerings can lead to users viewing only content that reinforces their own viewpoints without challenging them. Social media websites like Facebook may also present content in a way

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Some scholars have expressed concerns regarding the effects of filter bubbles on individual and social well-being, i.e. the dissemination of health information to the general public and the potential effects of internet search engines to alter health-related behavior. A 2019 multi-disciplinary book

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While algorithms do limit political diversity, some of the filter bubbles are the result of user choice. A study by data scientists at Facebook found that users have one friend with contrasting views for every four Facebook friends that share an ideology. No matter what Facebook's algorithm for its

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There are reports that Google and other sites maintain vast "dossiers" of information on their users, which might enable them to personalize individual internet experiences further if they choose to do so. For instance, the technology exists for Google to keep track of users' histories even if they

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identified a similar concept to filter bubbles as a "threat to democracy," i.e., the "retreat into our own bubbles, ...especially our social media feeds, surrounded by people who look like us and share the same political outlook and never challenge our assumptions... And increasingly, we become so

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and extremism. This can lead to users aggregating into homophilic clusters within social networks, which contributes to group polarization. "Echo chambers" reinforce an individual's beliefs without factual support. Individuals are surrounded by those who acknowledge and follow the same viewpoints,

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Hesse, Bradford W.; Nelson, David E.; Kreps, Gary L.; Croyle, Robert T.; Arora, Neeraj K.; Rimer, Barbara K.; Viswanath, Kasisomayajula (December 12, 2005). "Trust and Sources of Health Information: The Impact of the Internet and Its Implications for Health Care Providers: Findings From the First

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nudge users to read different perspectives if their reading pattern is biased towards one side/ideology. Although apps and plug-ins are tools humans can use, Eli Pariser stated "certainly, there is some individual responsibility here to really seek out new sources and people who aren't like you."

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add-on for Internet Explorer between March and May 2013. They selected 50,000 of those users who were active news consumers, then classified whether the news outlets they visited were left- or right-leaning, based on whether the majority of voters in the counties associated with user IP addresses

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Many people are unaware that filter bubbles even exist. This can be seen in an article in The Guardian, which mentioned the fact that "more than 60% of Facebook users are entirely unaware of any curation on Facebook at all, believing instead that every single story from their friends and followed

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Despite their differences, the usage of these terms go hand-in-hand in both academic and platform studies. It is often hard to distinguish between the two concepts in social network studies, due to limitations in accessibility of the filtering algorithms, that perhaps could enable researchers to

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is created by personalized algorithms; the content a user sees is filtered through an AI-driven algorithm that reinforces their existing beliefs and preferences, potentially excluding contrary or diverse perspectives. In this case, users have a more passive role and are perceived as victims of a

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This process is not random, as it operates under a three-step process, per Pariser, who states, "First, you figure out who people are and what they like. Then, you provide them with content and services that best fit them. Finally, you tune in to get the fit just right. Your identity shapes your

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are aimed to help people step out of their filter bubbles and make them aware of their personal perspectives; thus, these media show content that contradicts with their beliefs and opinions. In addition to plug-ins, there are apps created with the mission of encouraging users to open their echo

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theorized that this could have potentially positive implications for viewpoint diversity. These "friends" are often acquaintances with whom we would not likely share our politics without the internet. Facebook may foster a unique environment where a user sees and possibly interacts with content

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disputed the extent to which personalization filters distort Google search results, saying that "the effects of search personalization have been light." Further, Google provides the ability for users to shut off personalization features if they choose by deleting Google's record of their search

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I had friends Google BP when the oil spill was happening. These are two women who were quite similar in a lot of ways. One got a lot of results about the environmental consequences of what was happening and the spill. The other one just got investment information and nothing about the spill at

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Since web-based advertising can further the effect of the filter bubbles by exposing users to more of the same content, users can block much advertising by deleting their search history, turning off targeted ads, and downloading browser extensions. Some use anonymous or non-personalized search

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have been utilized by different researchers to test polarization and related effects that are attributed to filter bubbles and echo chambers. A 2018 study used social bots on Twitter to test deliberate user exposure to partisan viewpoints. The study claimed it demonstrated partisan differences

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in May 2011, in which he gave examples of how filter bubbles work and where they can be seen. In a test seeking to demonstrate the filter bubble effect, Pariser asked several friends to search for the word "Egypt" on Google and send him the results. Comparing two of the friends' first pages of

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is sponsoring inquiries into how filter bubbles affect people's ability to access diverse news. Additionally, it introduced a program aimed to educate citizens about social media. In the U.S., the CSCW panel suggests the use of news aggregator apps to broaden media consumers news intake. News

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as people assumed. The study also found that "individual choice," or confirmation bias, likewise affected what gets filtered out of News Feeds. Some social scientists criticized this conclusion because the point of protesting the filter bubble is that the algorithms and individual choice work

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Both "echo chambers" and "filter bubbles" describe situations where individuals are exposed to a narrow range of opinions and perspectives that reinforce their existing beliefs and biases, but there are some subtle differences between the two, especially in practices surrounding social media.

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concluded that "Individuals now have access to a wider span of viewpoints about news events, and most of this information is not coming through the traditional channels, but either directly from political actors or through their friends and relatives. Furthermore, the interactive nature of

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One driver and possible solution to the problem is the role of emotions in online content. A 2018 study shows that different emotions of messages can lead to polarization or convergence: joy is prevalent in emotional polarization, while sadness and fear play significant roles in emotional

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and a few others, Facebook has invested $ 14 million into efforts "to increase trust in journalism around the world, and to better inform the public conversation". The idea is that even if people are only reading posts shared from their friends, at least these posts will be credible.

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was performing her daily routine, which included drinking coffee when she opened her computer and noticed an advertisement for the same brand of coffee that she was drinking. "Sat down and opened up Facebook this morning while having my coffee, and there they were two ads for

3766:"NZZ is developing an app that gives readers personalised news without creating a filter bubble: The app uses machine learning to give readers a stream of 25 stories they might be interested in based on their preferences, but 'always including an element of surprise'" 544:. Kind of a 'whoa' moment when the product you're drinking pops up on the screen in front of you." "Whoa" moments occur when people are "found." Which means advertisement algorithms target specific users based on their "click behavior" to increase their sale revenue. 371:, and other services besides its search engine, although a contrary report was that trying to personalize the internet for each user, was technically challenging for an internet firm to achieve despite the huge amounts of available data. Analyst Doug Gross of 634:

is beta-testing a personalized news engine app which uses machine learning to guess what content a user is interested in, while "always including an element of surprise"; the idea is to mix in stories which a user is unlikely to have followed in the past.

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Mr Pariser's book provides a survey of the internet's evolution towards personalisation, examines how presenting information alters the way in which it is perceived and concludes with prescriptions for bursting the filter bubble that surrounds each

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Since December 4, 2009, Google has been personalized for everyone. So when I had two friends this spring Google "BP," one of them got a set of links that was about investment opportunities in BP. The other one got information about the oil

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As of 2011, one engineer had told Pariser that Google looked at 57 different pieces of data to personally tailor a user's search results, including non-cookie data such as the type of computer being used and the user's physical location.

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convergence. Since it is relatively easy to detect the emotional content of messages, these findings can help to design more socially responsible algorithms by starting to focus on the emotional content of algorithmic recommendations.

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Hilbert, M., Ahmed, S., Cho, J., Liu, B., & Luu, J. (2018). Communicating with Algorithms: A Transfer Entropy Analysis of Emotions-based Escapes from Online Echo Chambers. Communication Methods and Measures, 12(4), 260–275.

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study. The diagrams represent two aspects of the structure of filter bubbles, according to the study: large concentrations of users around single topics and a uni-directional, star-like structure that impacts key information

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compare and contrast the agencies of the two concepts. This type of research will continue to grow more difficult to conduct, as many social media networks have also begun to limit API access needed for academic research.

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pages appeared in their news feed." A brief explanation for how Facebook decides what goes on a user's news feed is through an algorithm that takes into account "how you have interacted with similar posts in the past."

3769: 2095:...if recommenders were perfect, I can have the option of talking to only people who are just like me....Cyber-balkanization, as Brynjolfsson coined the scenario, is not an inevitable effect of recommendation tools. 2082: 1495:...Trump's victory is blindsiding ... because, as media scholars understand it, we increasingly live in a "filter bubble": The information we take in is so personalized that we're blind to other perspectives.... 3796:"Bursting the filter bubble after the US election: Is the media doomed to fail? At an event in Brussels this week, media and politicians discussed echo chambers on social media and the fight against fake news" 448:

A study by Princeton University and New York University researchers aimed to study the impact of filter bubble and algorithmic filtering on social media polarization. They used a mathematical model called the

77:(2011), it was predicted that individualized personalization by algorithmic filtering would lead to intellectual isolation and social fragmentation. The bubble effect may have negative implications for civic 3742: 93:

have been associated with the influence of social media platforms such as Twitter and Facebook, and as a result have called into question the effects of the "filter bubble" phenomenon on user exposure to

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also found that these filters can create commonality, not fragmentation, in online music taste. Consumers reportedly use the filters to expand their taste rather than to limit it. Harvard law professor

267:, an echo chamber is a metaphorical description of a situation in which beliefs are amplified or reinforced by communication and repetition inside a closed system. Based on the sociological concept of 62:

However, there are conflicting reports about the extent to which personalized filtering happens and whether such activity is beneficial or harmful, with various studies producing inconclusive results.

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found that user data used to play a bigger role in determining search results but that Google, through testing, found that the search query is by far the best determinant of what results to display.

4322: 279:, which describes all processes in which users of a given platform can actively opt in and out of information consumption, such as a user's ability to follow other users or select into groups. 3812:... EU referendum in the UK on a panel at the "Politicians in a communication storm" event... On top of the filter bubble, partisan Facebook pages also served up a diet heavy in fake news.... 2405:

Elanor Colleoni; Alessandro Rozza; Adam Arvidsson (April 2014). "Echo Chamber or Public Sphere? Predicting Political Orientation and Measuring Political Homophily in Twitter Using Big Data".

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goes beyond self-interests. Fostering one's bridging capital, such as by connecting with more people in an informal setting, may be an effective way to reduce the filter bubble phenomenon.

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There are conflicting reports about the extent to which personalized filtering happens and whether such activity is beneficial or harmful. Analyst Jacob Weisberg, writing in June 2011 for

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Nguyen, Tien T.; Hui, Pik-Mai; Harper, F. Maxwell; Terveen, Loren; Konstan, Joseph A. (2014). "Exploring the filter bubble: The effect of using recommender systems on content diversity".

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until a later time, prompting a larger problem that exists still: whether the search engine acts either as an arbiter of truth or as a knowledgeable guide by which to make decisions by.

4157: 3034:"Age, gender, personality, ideological attitudes and individual differences in a person's news spectrum: how many and who might be prone to 'filter bubbles' and 'echo chambers' online?" 1461:...The global village that was once the internet ... digital islands of isolation that are drifting further apart each day ... your experience online grows increasingly personalized ... 4654: 385:, and would help a consumer looking for "pizza" find local delivery options based on a personalized search and appropriately filter out distant pizza stores. Organizations such as the 4191: 1149:

By tracking individual Web browsers with cookies, Google has been able to personalize results even for users who don't create a personal Google account or are not logged into one. ...

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secure in our bubbles that we start accepting only information, whether it's true or not, that fits our opinions, instead of basing our opinions on the evidence that is out there."

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don't have a personal Google account or are not logged into one. One report stated that Google had collected "10 years' worth" of information amassed from varying sources, such as

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Hosanagar, Kartik; Fleder, Daniel; Lee, Dokyun; Buja, Andreas (December 2013). "Will the Global Village Fracture into Tribes: Recommender Systems and their Effects on Consumers".

397:, and others have experimented with creating new personalized information services, with the aim of tailoring search results to those that users are likely to like or agree with. 4523: 1482: 1407:"Eli Pariser: activist whose filter bubble warnings presaged Trump and Brexit: Upworthy chief warned about dangers of the internet's echo chambers five years before 2016's votes" 1342: 3195: 786:

Researches explain that the filter bubble reinforces what one is already thinking. This is why it is extremely important to utilize resources that offer various points of view.

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Resnick, Paul; Garrett, R. Kelly; Kriplean, Travis; Munson, Sean A.; Stroud, Natalie Jomini (2013). "Bursting your (Filter) bubble: Strategies for promoting diverse exposure".

4086: 3928: 3650: 3134: 2976: 1614: 3765: 4225: 3782:... if, based on their consumption history, someone has not expressed an interest in sports, their stream will include news about big, important stories related to sports,... 1975: 6948: 3103: 3799: 1566:

Haim, Mario; Arendt, Florian; Scherr, Sebastian (February 2017). "Abyss or Shelter? On the Relevance of Web Search Engines' Search Results When People Google for Suicide".

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Del Vicario, Michela; Bessi, Alessandro; Zollo, Fabiana; Petroni, Fabio; Scala, Antonio; Caldarelli, Guido; Stanley, H. Eugene; Quattrociocchi, Walter (January 19, 2016).

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Since the content seen by individual social media users is influenced by algorithms that produce filter bubbles, users of social media platforms are more susceptible to

326:, did a small non-scientific experiment to test Pariser's theory which involved five associates with different ideological backgrounds conducting a series of searches, " 4621: 195:

A world constructed from the familiar is a world in which there's nothing to learn ... (since there is) invisible autopropaganda, indoctrinating us with our own ideas.

3712: 6194: 2119: 1427:..."If you only see posts from folks who are like you, you're going to be surprised when someone very unlike you wins the presidency," Pariser tells The Guardian.... 424: 2892: 1904: 1302: 1032: 6030: 6025: 6020: 4999:

Liao, Q. Vera; Fu, Wai-Tat (2013). "Beyond the filter bubble: Interactive effects of perceived threat and topic involvement on selective exposure to information".

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results, while there was overlap between them on topics like news and travel, one friend's results prominently included links to information on the then-ongoing

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Though the study found that only about 15–20% of the average user's Facebook friends subscribe to the opposite side of the political spectrum, Julia Kaman from

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leads the initiative, striving to combat misinformation, with a specific focus on the product with regards to literacy, research and creative interventions.

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than those users who essentially self-select their bias through their choice of news publications (assuming they are aware of the publications' biases).

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used to construct filter bubbles are expected to become more widespread. Scholars have begun considering the effect of filter bubbles on the users of

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Zhang, Yuan Cao; Séaghdha, Diarmuid Ó; Quercia, Daniele; Jambor, Tamas (2012). "Auralist: Introducing serendipity into music recommendation".

949:, referring to that region of Europe that was historically subdivided by languages, religions and cultures; the term was coined in a paper by 238:

belong at social events unless those events were especially planned to be appealing for children and unappealing for adults without children.

159:

Accessing the data of link clicks displayed through site traffic measurements determines that filter bubbles can be collective or individual.

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Pariser explains that feeding us only what is familiar and comfortable to us closes us off to new ideas, subjects and important information.

282:

In an echo chamber, people are able to seek out information that reinforces their existing views, potentially as an unconscious exercise of

6201: 3313: 576:, internet activist Eli Pariser highlights how the increasing occurrence of filter bubbles further emphasizes the value of one's bridging 6938: 6243: 6184: 191:

they have the possibility of "undermining civic discourse" and making people more vulnerable to "propaganda and manipulation." He wrote:

4833: 3529: 5998: 5890: 5557: 1474: 1334: 1081:"Understanding Echo Chambers and Filter Bubbles: The Impact of Social Media on Diversification and Partisan Shifts in News Consumption" 977: 3187: 5530: 4078: 3850:

Resnick, Paul; Garrett, R. Kelly; Kriplean, Travis; Munson, Sean A.; Stroud, Natalie Jomini (2013). "Bursting your (Filter) bubble".

3828: 3642: 3126: 2972: 2005: 4217: 3384: 5111: 2338:

Cinelli, Matteo; De Francisci Morales, Gianmarco; Galeazzi, Alessandro; Quattrociocchi, Walter; Starnini, Michele (March 2, 2021).

1967: 755: 4788: 3095: 2179: 6916: 6211: 6042: 6005: 5603: 3795: 4055: 2844: 2245: 5960: 5613: 4785:"Filter Bubbles & Confirmation Bias - Fake News (And how to fight it) - LibGuides at Miami Dade College Learning Resources" 7033: 6440: 5894: 4826: 4430:

Reviglio, Urbano (June 2019). "Serendipity as an emerging design principle of the infosphere: challenges and opportunities".

4384: 3867: 3601: 2582: 2287: 950: 89:, noting that the two search results pages were "strikingly different" despite use of the same key words. The results of the 4613: 114: 4344:

Borgesius, Frederik; Trilling, Damian; Möller, Judith; Bodó, Balázs; de Vreese, Claes; Helberger, Natali (March 31, 2016).

3704: 2111: 7008: 6164: 5567: 5374: 2884: 1896: 1294: 1029: 432:

A study by Oxford, Stanford, and Microsoft researchers examined the browsing histories of 1.2 million U.S. users of the

6070: 5635: 3510:

Bucher, Taina (February 25, 2016). "The algorithmic imaginary: exploring the ordinary effects of Facebook algorithms".

2313: 241: 4467:"Democratizing algorithmic news recommenders: how to materialize voice in a technologically saturated media ecosystem" 3157: 1049: 7013: 6717: 5852: 5465: 5016: 4981: 4946: 4728: 3955: 3626: 2074: 1726: 1694: 1178: 892: 724:

Technologists, social media engineers, and computer specialists have also examined the prevalence of filter bubbles.

441:

active news consumers may get most of their news via social media, and thus experience stronger effects of social or

2818:

Chitra, Uthsav; Musco, Christopher (2020). "Analyzing the Impact of Filter Bubbles on Social Network Polarization".

2629: 2142: 1650: 32:

Social media inadvertently isolates users into their own ideological filter bubbles, according to internet activist

7136: 7096: 6712: 6529: 6433: 6405: 5750: 4751: 4345: 1208: 470:

The Facebook study found that it was "inconclusive" whether or not the algorithm played as big a role in filtering

2781:

Flaxman, Seth; Goel, Sharad; Rao, Justin M. (2016). "Filter Bubbles, Echo Chambers, and Online News Consumption".

6223: 5552: 5520: 3555: 6233: 6206: 6143: 5662: 4400: 3985: 1615:"Medical Misinformation and Social Harm in Non-Science Based Health Practices: A Multidisciplinary Perspective" 1129:"Your Results May Vary: Will the information superhighway turn into a cul-de-sac because of automated filters?" 463: 1266: 6340: 6084: 5965: 5771: 718: 552: 275:

in a hollow enclosure. With regard to social media, this sort of situation feeds into explicit mechanisms of

90: 4184:"Mark Zuckerberg's manifesto: How Facebook will connect the world, beat fake news and pop the filter bubble" 7121: 7101: 7043: 6943: 6754: 6593: 6238: 5993: 5900: 5272: 5104: 1128: 3895: 6894: 6554: 6534: 6350: 6345: 5795: 5582: 5577: 5282: 5187: 2698: 2075:"Systems hope to tell you what you'd like: 'Preference engines' guide users through the flood of content" 674: 172: 86: 1929: 1860:"First Monday: What's on tap this month on TV and in movies and books: The Filter Bubble by Eli Pariser" 7111: 6889: 6360: 5790: 5233: 5146: 3617:

Stephen Baron; John Field; Tom Schuller (November 30, 2000). "Social capital: A review and critique.".

817: 140: 56: 7131: 7003: 6277: 6253: 5317: 5083: 4524:"Inside Facebook's (Totally Insane, Unintentionally Gigantic, Hyperpartisan) Political-Media Machine" 1917:

When it comes to content, Google and Facebook are offering us too much candy, and not enough carrots.

1827: 1800: 897: 677:'s "News Integrity Initiative," poised at eliminating fake news and creating more honest news media. 268: 20: 4284: 3332:

Bail, Christopher; Argyle, Lisa; Brown, Taylor; Chen, Haohan; Hunzaker, M.B.F.; Lee, Jaemin (2018).

3283: 2030:

Van Alstyne, Marshall; Brynjolfsson, Erik (November 1996). "Could the Internet Balkanize Science?".

1440: 102:, spurring new interest in the term, with many concerned that the phenomenon may harm democracy and 7075: 7053: 6933: 6856: 6365: 6179: 6047: 5176: 1748:

Nikolov, Dimitar; Oliveira, Diego F.M.; Flammini, Alessandro; Menczer, Filippo (December 2, 2015).

589:

sites to identify fake news. Technology can also play a valuable role in combating filter bubbles.

4471:

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

3673: 3593: 3276:"How Social Media Reduces Mass Political Polarization. Evidence from Germany, Spain, and the U.S." 419:

history and setting Google not to remember their search keywords and visited links in the future.

7126: 7028: 6481: 6291: 6248: 6130: 6120: 5608: 5472: 5411: 5213: 5097: 2314:"What are Filter Bubbles and Digital Echo Chambers? | Heinrich-Böll-Stiftung | Tel Aviv - Israel" 2279: 501: 3735:"A news app aims to burst filter bubbles by nudging readers toward a more "balanced" media diet" 7018: 6881: 6809: 6774: 6491: 5988: 5950: 5915: 5640: 5381: 5297: 3310: 3278: 2267: 857: 832: 450: 4012:"The Mozilla Information Trust Initiative: Building a movement to fight misinformation online" 3852:

Proceedings of the 2013 conference on Computer supported cooperative work companion - CSCW '13

2610: 6981: 6861: 6749: 6739: 6722: 6678: 6576: 6496: 6456: 6333: 6138: 5927: 5723: 5645: 5630: 5525: 5457: 5449: 5386: 5342: 5312: 5277: 5203: 2642:

Google customizing search results is an automatic feature, but you can shut this feature off.

3585: 1367:

DiFranzo, Dominic; Gloria-Garcia, Kristine (April 5, 2017). "Filter bubbles and fake news".

974: 6998: 6901: 6804: 6744: 6653: 6648: 6544: 6486: 6471: 6052: 5620: 4692: 4566: 4478: 4150:"The Filter Bubble raises important issues – You just need to filter them out for yourself" 3435: 3348: 3230: 3045: 2927: 2549:"Twitter's plan to cut off free data access evokes 'fair amount of panic' among scientists" 2492: 2351: 2039: 1771: 852: 842: 827: 822: 812: 254: 136: 99: 52: 3824: 1998: 585:

that are unverifiable or weak. Chris Glushko, the VP of Marketing at IAB, advocates using

511: 8: 7116: 6911: 6841: 6380: 6115: 5945: 5733: 5650: 5587: 5337: 4377:

The Filter Bubble: How the New Personalized Web is Changing What We Read and How We Think

3586: 3333: 3032:

Sindermann, Cornelia; Elhai, Jon D.; Moshagen, Morten; Montag, Christian (January 2020).

1686:

The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think

771: 639: 593: 491: 287: 48: 4696: 4570: 4482: 3439: 3352: 3234: 3049: 2931: 2820:

WSDM '20: Proceedings of the 13th International Conference on Web Search and Data Mining

2493:"Thinking Outside the Black-Box: The Case for "Algorithmic Sovereignty" in Social Media" 2355: 2043: 1775: 547:

Several designers have developed tools to counteract the effects of filter bubbles (see

6986: 6729: 6707: 6702: 6620: 6615: 6571: 5821: 5811: 5625: 5479: 5352: 5327: 5166: 5060: 5035: 5022: 4987: 4952: 4917: 4784: 4589: 4554: 4499: 4466: 4447: 4131: 3900: 3873: 3456: 3425: 3413: 3371: 3256: 3068: 3033: 2953: 2798: 2718: 2530: 2473: 2382: 2339: 2272: 2207: 2171: 2055: 1761: 1591: 1538: 1513: 1384: 1184: 1100: 1011: 909: 862: 410: 393: 19:"Social media bubble" redirects here. For the technology boom and bust phenomenon, see 2235: 126:

Pariser defined his concept of a filter bubble in more formal terms as "that personal

6906: 6866: 6819: 6643: 6625: 6513: 6258: 5940: 5421: 5401: 5369: 5250: 5228: 5183: 5151: 5065: 5012: 4977: 4942: 4912: 4895: 4822: 4594: 4504: 4380: 4265: 4135: 4048:"Values in the filter bubble Ethics of Personalization Algorithms in Cloud Computing" 4047: 3863: 3622: 3597: 3461: 3376: 3260: 3248: 3073: 2957: 2945: 2722: 2606: 2578: 2534: 2522: 2477: 2465: 2387: 2369: 2283: 1690: 1583: 1543: 1174: 1104: 994:

Bozdag, Engin (September 2013). "Bias in algorithmic filtering and personalization".

882: 740: 638:

The European Union is taking measures to lessen the effect of the filter bubble. The

623: 415: 299: 283: 231: 82: 5089: 4991: 4956: 4921: 4451: 3877: 2059: 1671:

a filter bubble is the figurative sphere surrounding you as you search the Internet.

1015: 797: 6928: 6824: 6814: 6586: 6503: 5540: 5515: 5364: 5332: 5257: 5055: 5047: 5026: 5004: 4969: 4966:

Proceedings of the 2013 conference on Computer supported cooperative work companion

4934: 4907: 4880: 4700: 4584: 4574: 4494: 4486: 4439: 4257: 4121: 3855: 3451: 3443: 3366: 3356: 3238: 3188:"Contrary to what you've heard, Facebook can help puncture our political "bubbles"" 3063: 3053: 2935: 2823: 2803: 2790: 2761: 2710: 2677: 2667: 2512: 2504: 2455: 2422: 2414: 2377: 2359: 2047: 1832: 1779: 1595: 1575: 1533: 1525: 1388: 1376: 1188: 1166: 1163:

Proceedings of the fifth ACM international conference on Web search and data mining

1092: 1003: 877: 847: 710: 442: 354: 4126: 4109: 3481:"Google personalizes search results even when you're logged out, new study claims" 3058: 2051: 1579: 515:

Visualization of the process and growth of two social media bots used in the 2019

6846: 6673: 6148: 5935: 5699: 5535: 5347: 4261: 3317: 3306: 2337: 1096: 1036: 981: 803: 725: 694: 387: 3334:"Exposure to opposing views on social media can increase political polarization" 3299: 2444:"Self-imposed filter bubbles: Selective attention and exposure in online search" 758:

scholars have likewise expressed concerns about the effect of filter bubbles on

630:

in order to prevent companies from gathering their web-search data. Swiss daily

6876: 6791: 6781: 6769: 6685: 6658: 6603: 6549: 6228: 6110: 5738: 5391: 5171: 5161: 5124: 5120: 2460: 2443: 748: 744: 577: 322: 4885: 4868: 4705: 4680: 4443: 2750:"A critical review of filter bubbles and a comparison with selective exposure" 2442:

Ekström, Axel G.; Niehorster, Diederick C.; Olsson, Erik J. (August 1, 2022).

1722: 1007: 7090: 6976: 6851: 6697: 6508: 6370: 6328: 5718: 5322: 5262: 4818: 3929:"Facebook Tweaks its 'Trending Topics' Algorithm to Better Reflect Real News" 2714: 2526: 2508: 2469: 2404: 2373: 945: 902: 887: 619: 586: 479: 272: 202: 175:, while the other friend's first page of results did not include such links. 139:

to the user, or make certain types of information appear more prominently in

28: 5051: 5008: 4973: 4938: 4579: 4465:

Harambam, Jaron; Helberger, Natali; van Hoboken, Joris (November 28, 2018).

3859: 3361: 3243: 3218: 2940: 2915: 2827: 2364: 1529: 1170: 220:

A filter bubble has been described as exacerbating a phenomenon that called

7070: 7058: 6759: 6539: 5970: 5864: 5756: 5416: 5069: 4614:"Facebook and Cambridge Analytica: What You Need to Know as Fallout Widens" 4598: 4508: 4490: 4269: 3465: 3380: 3252: 3077: 2949: 2391: 1587: 1547: 1259:"Bubble Trouble: Is Web personalization turning us into solipsistic twits?" 837: 702: 496: 433: 331: 327: 6425: 5001:

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

4720: 2766: 2749: 767:" and how this may influence political leaning, including how users vote. 271:, the term is a metaphor based on the acoustic echo chamber, where sounds 234:" and "the figurative sphere surrounding you as you search the internet." 6834: 6764: 6598: 6476: 6263: 5743: 5728: 5572: 5287: 5238: 5208: 3581: 2794: 2672: 2655: 1475:"The 'Filter Bubble' Explains Why Trump Won and You Didn't See It Coming" 1335:"The 'Filter Bubble' Explains Why Trump Won and You Didn't See It Coming" 662: 381: 368: 222: 131: 70: 33: 5036:"The filter bubble and its effect on online personal health information" 4645:"Facebook-Cambridge Analytica: A timeline of the data hijacking scandal" 3447: 2682: 1784: 1749: 1514:"The filter bubble and its effect on online personal health information" 291:

but they also possess the agency to break outside of the echo chambers.

7048: 7038: 6796: 6581: 6566: 6559: 6460: 6390: 5840: 5816: 5547: 5406: 5396: 5359: 5292: 5267: 4315:"How to Burst the "Filter Bubble" that Protects Us from Opposing Views" 2626:"Google Personalization on Your Search Results Plus How to Turn it Off" 2517: 2427: 2418: 1968:"How social media filter bubbles and algorithms influence the election" 915: 867: 661:

seeking to combat this. By training its search engine to recognize the

653: 611: 524: 264: 103: 5876: 3674:"Pop the Personalization Filter Bubbles and Preserve Online Diversity" 2575:

The Big Bubble: How Technology Makes It Harder to Understand the World

6734: 6668: 6635: 6385: 6375: 6094: 5785: 5307: 5223: 5198: 5193: 3412:

Min, Yong; Jiang, Tingjun; Jin, Cheng; Li, Qu; Jin, Xiaogang (2019).

2240: 1897:"Facebook, Google Giving Us Information Junk Food, Eli Pariser Warns" 872: 764: 759: 698: 541: 471: 339: 335: 127: 95: 78: 4108:

Haim, Mario; Graefe, Andreas; Brosius, Hans-Bernd (March 16, 2018).

2699:"Redefining Filter Bubbles as (Escapable) Socio-Technical Recursion" 2274:

Echo Chamber: Rush Limbaugh and the Conservative Media Establishment

1380: 1362: 1360: 1079:

Kitchens, Brent; Johnson, Steve L.; Gray, Peter (December 1, 2020).

673:, and Craigslist contributed to the majority of a $ 14M donation to 7063: 6690: 6608: 6410: 6400: 6296: 6125: 3986:"Facebook, Mozilla and Craigslist Craig fund fake news firefighter" 3643:"Are we stuck in filter bubbles? Here are five potential paths out" 3616: 3430: 2112:"Why are American kids treated as a different species from adults?" 1766: 1258: 714: 376: 344: 187: 167: 4931:

Proceedings of the 23rd international conference on World wide web

1651:"Algorithms and the Filter Bubble Ruining Your Online Experience?" 7023: 6829: 6663: 6090:

Media censorship and disinformation during the Gezi Park protests

5955: 5826: 5245: 5218: 5156: 4721:"How Filter Bubbles Distort Reality: Everything You Need to Know" 3896:"Facebook Tests Related Articles Feature to Fight Filter Bubbles" 3127:"Why Scientists Are Upset About The Facebook Filter Bubble Study" 2973:"Why Scientists Are Upset About The Facebook Filter Bubble Study" 1723:"How Filter Bubbles Distort Reality: Everything You Need to Know" 1357: 681: 670: 559:(the German translation of filter bubble) word of the year 2016. 487: 3219:"Exposure to ideologically diverse news and opinion on Facebook" 2916:"Exposure to ideologically diverse news and opinion on Facebook" 375:

suggested that filtered searching seemed to be more helpful for

6395: 4838: 706: 183: 73:

circa 2010. In Pariser's influential book under the same name,

2236:"John Gorenfeld, Moon the Messiah, and the Media Echo Chamber" 1747: 286:. This sort of feedback regulation may increase political and 166:

Pariser's idea of the filter bubble was popularized after the

6189: 3031: 2845:"5 Questions with Eli Pariser, Author of 'The Filter Bubble'" 2172:"Blame the Echo Chamber on Facebook. But Blame Yourself, Too" 1030:

The Huffington Post "Are Filter-bubbles Shrinking Our Minds?"

627: 615: 364: 294:

On the other hand, filter bubbles are implicit mechanisms of

4963: 4896:"Social Network Sites: Definition, History, and Scholarship" 4552: 4464: 3956:"Google is finally admitting it has a filter-bubble problem" 3849: 3311:

https://www.martinhilbert.net/communicating-with-algorithms/

751:

are also anticipated as a result of personalized filtering.

5302: 4649: 4343: 3414:"Endogenetic structure of filter bubble in social networks" 607: 1160: 47:

is a state of intellectual isolation that can result from

3530:"How do we break filter bubble and design for democracy?" 1999:"Electronic Communities: Global Village or Cyberbalkans?" 1997:

Van Alstyne, Marshall; Brynjolfsson, Erik (March 1997) .

372: 4079:"The Many Ethical Implications of Emerging Technologies" 3158:"Did Facebook's Big Study Kill My Filter Bubble Thesis?" 743:, and may be exposed to biased, misleading information. 122:

was coined by internet activist Eli Pariser, circa 2010.

4815:

The Filter Bubble: What the Internet Is Hiding from You

3588:

The Filter Bubble: What the Internet Is Hiding from You

2914:

Bakshy, E.; Messing, S.; Adamic, L. A. (June 5, 2015).

2441: 2029: 1996: 574:

The Filter Bubble: What the Internet Is Hiding from You

4928: 4867:

Bozdag, Engin; van den Hoven, Jeroen (December 2015).

4246: 2600: 5487:

After Truth: Disinformation and the Cost of Fake News

5119: 3096:"Fun facts from the new Facebook filter bubble study" 2066: 1438: 1366: 6356:

Countering Foreign Propaganda and Disinformation Act

5684: 4177: 4175: 793: 4894:boyd, danah m.; Ellison, Nicole B. (October 2007). 4866: 4041: 4039: 4037: 3331: 3216: 2913: 2883:Bleiberg, Joshua; West, Darrell M. (May 24, 2017). 2072: 1078: 85:, while another searcher got information about the 5459:Dezinformatsia: Active Measures in Soviet Strategy 4869:"Breaking the filter bubble: democracy and design" 2271: 728:, founder of Facebook, and Eli Pariser, author of 16:Intellectual isolation through internet algorithms 6011:Disinformation in the Russian invasion of Ukraine 5563:Disinformation in the Russian invasion of Ukraine 4779: 4777: 4211: 4209: 4172: 4107: 1400: 1398: 1050:"What Are Filter Bubbles & How To Avoid Them" 400: 59:results and Facebook's personalized news-stream. 7088: 5906:Historical distortion regarding Ferdinand Marcos 4034: 3793: 3763: 2491:Reviglio, Urbano; Agosti, Claudio (April 2020). 2266: 1565: 248: 4559:Proceedings of the National Academy of Sciences 3341:Proceedings of the National Academy of Sciences 3217:Bakshy, E.; Messing, S.; Adamic, L. A. (2015). 2344:Proceedings of the National Academy of Sciences 2308: 2306: 106:by making the effects of misinformation worse. 4774: 4206: 3889: 3887: 3787: 3757: 2780: 2490: 1404: 1395: 6441: 6219:Election denial movement in the United States 5105: 4834:"Breaking Out of Your Internet Filter Bubble" 3411: 3300:https://doi.org/10.1080/19312458.2018.1479843 4285:"Your filter bubble is destroying democracy" 4248:Health Information National Trends Survey". 3556:""Filterblase" ist das Wort des Jahres 2016" 2882: 2303: 2073:Alex Pham; Jon Healey (September 24, 2005). 1930:"Invisible sieve: Hidden, specially for you" 1466: 1441:"Your Filter Bubble is Destroying Democracy" 967: 6939:Political polarization in the United States 6455: 5439: 4893: 4045: 3884: 3580: 2817: 1439:Mostafa M. El-Bermawy (November 18, 2016). 1432: 669:In April 2017 news surfaced that Facebook, 500:bubbles and their ability to create deeper 6448: 6434: 5891:COVID-19 misinformation in the Philippines 5112: 5098: 4900:Journal of Computer-Mediated Communication 4282: 2577:. United Stories Publishing. p. 179. 1472: 975:Definition – What does Filter Bubble mean? 6992:Facebook–Cambridge Analytica data scandal 5059: 4911: 4884: 4704: 4611: 4588: 4578: 4498: 4283:El-Bermawy, Mostafa (November 18, 2016). 4125: 3455: 3429: 3370: 3360: 3282: 3242: 3067: 3057: 2939: 2802: 2765: 2681: 2671: 2596: 2594: 2572: 2516: 2459: 2426: 2381: 2363: 2340:"The echo chamber effect on social media" 2169: 2109: 1890: 1888: 1783: 1765: 1644: 1642: 1640: 1537: 1288: 1286: 1284: 1206: 953:researchers Van Alstyne and Brynjolfsson. 939:(sometimes with a hyphen) is a hybrid of 905:discovery, an antithesis of filter bubble 680:Later, in August, Mozilla, makers of the 6244:Mohamed Atta's alleged Prague connection 4853: 4642: 4555:"The spreading of misinformation online" 4429: 4181: 3702: 3518:– via Taylor & Francis Online. 3512:Information, Communication & Society 2747: 1256: 1252: 1250: 1248: 1246: 1244: 1242: 1240: 1238: 1202: 1200: 1198: 1122: 1120: 1118: 1116: 1114: 510: 310: 215: 113: 27: 6043:Russian Institute for Strategic Studies 4521: 4374: 4346:"Should we worry about filter bubbles?" 4215: 3908:from the original on September 25, 2017 3705:"Try Breaking Your Media Filter Bubble" 3671: 3273: 3155: 3093: 2774: 2748:Dahlgren, Peter M. (January 29, 2021). 2270:; Cappella, Joseph N. 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"Going Viral". 4831: 4791:from the original on October 23, 2020 4678: 4657:from the original on October 19, 2018 4624:from the original on October 19, 2018 4534:from the original on October 19, 2017 4411:from the original on January 15, 2019 4325:from the original on January 19, 2021 4076: 4022:from the original on January 14, 2019 3619:Social Capital: Critical perspectives 3478: 3137:from the original on October 23, 2017 3089: 3087: 3010:from the original on February 6, 2020 2895:from the original on October 10, 2017 2878: 2876: 2874: 2872: 2870: 2839: 2837: 2729:from the original on January 19, 2021 2653: 2151:from the original on January 24, 2017 2140: 2085:from the original on December 8, 2015 1703:from the original on January 19, 2021 1648: 1609: 1607: 1605: 1561: 1559: 1557: 1507: 1505: 1503: 1328: 1326: 1324: 1292: 1235: 1195: 1111: 1048:Encrypt, Search (February 26, 2019). 646: 7107:Internet manipulation and propaganda 4762:from the original on August 22, 2017 4750:Dish, The Daily (October 10, 2010). 4749: 4182:Sterling, Greg (February 20, 2017). 3715:from the original on August 21, 2017 3703:Ritholtz, Barry (February 2, 2017). 3124: 2970: 2885:"Political polarization on Facebook" 2201:DiFonzo, Nicholas (April 21, 2011). 1965: 1956: 1219:from the original on August 22, 2017 1207:Parramore, Lynn (October 10, 2010). 548: 7009:Digital media use and mental health 6165:1995 CIA disinformation controversy 5375:State-sponsored Internet propaganda 4681:"The dangers of a post-truth world" 4669: 4612:Granville, Kevin (March 19, 2018). 4356:from the original on March 20, 2017 3894:Vanian, Jonathan (April 25, 2017). 3802:from the original on March 10, 2017 3684:from the original on March 15, 2017 3672:Glushko, Chris (February 8, 2017). 3592:. 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News apps such as 411:personalized recommendations 296:pre-selected personalization 7: 6555:Least objectionable program 6351:Counter Misinformation Team 6346:Counter disinformation unit 5796:Myth of the clean Wehrmacht 5283:Forgery as covert operation 4379:. New York: Penguin Press. 3621:. Oxford University Press. 3125:Lumb, David (May 8, 2015). 2147:(Speech). Washington, D.C. 1826:Pariser, Eli (March 2011). 1799:Pariser, Eli (March 2011). 789: 173:Egyptian revolution of 2011 87:Deepwater Horizon oil spill 10: 7153: 6890:Algorithmic radicalization 6361:The Disinformation Project 5791:Propaganda in Nazi Germany 5147:Algorithmic radicalization 4856:Columbia Journalism Review 4401:"In praise of serendipity" 3931:. KQED Public Media. NPR. 3418:Royal Society Open Science 2461:10.1016/j.chbr.2022.100226 818:Algorithmic radicalization 777: 252: 109: 57:Google Personalized Search 18: 7004:Cultural impact of TikTok 6969: 6875: 6790: 6634: 6522: 6467: 6324: 6313: 6284: 6278:Bolivarian Army of Trolls 6272: 6254:Tobacco industry playbook 6185:CIA Kennedy assassination 6157: 6103: 6077: 6065: 5979: 5926: 5914: 5883: 5871: 5859: 5847: 5835: 5804: 5778: 5766: 5706: 5694: 5690: 5679: 5511: 5500: 5445: 5434: 5318:Manipulation (psychology) 5142: 5136: 5131: 4886:10.1007/s10676-015-9380-y 4706:10.1016/j.cub.2016.12.034 4444:10.1007/s10676-018-9496-y 4154:Rainforest Action Network 2203:"The Echo-Chamber Effect" 1008:10.1007/s10676-013-9321-6 898:Selective exposure theory 269:selective exposure theory 153:Wall Street Journal study 21:Social media stock bubble 7076:Violence and video games 7054:Social impact of YouTube 6934:Knowledge gap hypothesis 6857:Social-desirability bias 6755:Information–action ratio 6366:East StratCom Task Force 6180:9/11 conspiracy theories 5177:List of cognitive biases 5040:Croatian Medical Journal 2783:Public Opinion Quarterly 2715:10.1177/1360780418763824 2509:10.1177/2056305120915613 2407:Journal of Communication 1518:Croatian Medical Journal 1097:10.25300/MISQ/2020/16371 922: 749:discriminatory practices 747:and other unintentional 697:increases, personalized 405:A scientific study from 7137:Sociology of technology 7097:Influence of mass media 7029:Mass shooting contagion 6482:Evolutionary psychology 6292:Public opinion brigades 6249:Niger uranium forgeries 6239:Litter boxes in schools 5609:COVID-19 misinformation 5531:Free energy suppression 5440:Books and documentaries 5214:Euphemistic misspeaking 5086:. 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Archived from 2503:(2): 205630512091561. 2497:Social Media + Society 2318:Heinrich-Böll-Stiftung 1754:PeerJ Computer Science 858:False consensus effect 833:Communal reinforcement 549:§ Countermeasures 521: 502:political polarization 486:Similarly, a study of 451:stochastic block model 425:Internet Policy Review 209: 157: 123: 36: 6982:Criticism of Facebook 6862:Social influence bias 6750:Information pollution 6740:Information explosion 6723:Texting while driving 6679:Low information voter 6577:Pink-slime journalism 6334:Fact-checking website 6139:Operation Mass Appeal 6121:Clockwork Orange plot 5631:Mental illness denial 5526:Climate change denial 5343:Psychological warfare 5313:Internet manipulation 5278:Firehose of falsehood 5204:Disinformation attack 4375:Pariser, Eli (2011). 4319:MIT Technology Review 3825:"European Commission" 2889:Brookings Institution 2767:10.2478/nor-2021-0002 2234:sdf (June 23, 2004). 1966:Hern (May 22, 2017). 693:As the popularity of 599:Read Across the Aisle 514: 490:'s filter bubbles by 311:Reactions and studies 253:Further information: 216:Extensions of concept 193: 149: 117: 49:personalized searches 31: 6999:Criticism of Netflix 6805:Availability cascade 6745:Information overload 6654:Attention management 6649:Attention inequality 6545:Human-interest story 6487:Behavioral modernity 6472:Cognitive psychology 5473:Who's Who in the CIA 4933:. pp. 677–686. 3798:. 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July 31, 2017. 4407:. March 9, 2017. 4386:978-1-59420-300-8 3869:978-1-4503-1332-2 3603:978-1-59420-300-8 3532:. March 3, 2017. 3347:(37): 9216–9221. 2584:978-91-639-5990-5 2289:978-0-19-536682-2 1936:. June 30, 2011. 1725:. July 31, 2017. 1479:New York Magazine 1028:Huffington Post, 883:Media consumption 741:confirmation bias 730:The Filter Bubble 416:Jonathan Zittrain 300:media consumption 298:, where a user's 284:confirmation bias 180:The Filter Bubble 151:According to one 83:British Petroleum 75:The Filter Bubble 45:ideological frame 7144: 7132:Social influence 6929:Knowledge divide 6825:Crowd psychology 6815:Bandwagon effect 6587:Public relations 6504:Media psychology 6450: 6443: 6436: 6427: 6426: 6315: 6314: 6134:MMR autism fraud 6017:On US elections 5951:Operation Toucan 5924: 5923: 5692: 5691: 5681: 5680: 5646:anti-vaccination 5594: 5593: 5541:Holocaust denial 5516:Bermuda Triangle 5502: 5501: 5436: 5435: 5365:black propaganda 5333:Potemkin village 5258:False accusation 5234:list of websites 5133: 5132: 5114: 5107: 5100: 5091: 5090: 5073: 5063: 5030: 4995: 4960: 4925: 4915: 4890: 4888: 4863: 4850: 4848: 4846: 4801: 4800: 4798: 4796: 4781: 4772: 4771: 4769: 4767: 4747: 4741: 4740: 4738: 4736: 4717: 4711: 4710: 4708: 4676: 4667: 4666: 4664: 4662: 4640: 4634: 4633: 4631: 4629: 4609: 4603: 4602: 4592: 4582: 4550: 4544: 4543: 4541: 4539: 4519: 4513: 4512: 4502: 4462: 4456: 4455: 4427: 4421: 4420: 4418: 4416: 4397: 4391: 4390: 4372: 4366: 4365: 4363: 4361: 4341: 4335: 4334: 4332: 4330: 4311: 4305: 4304: 4302: 4300: 4280: 4274: 4273: 4244: 4238: 4237: 4235: 4233: 4218:"Your Own Facts" 4213: 4204: 4203: 4201: 4199: 4179: 4170: 4169: 4167: 4165: 4146: 4140: 4139: 4129: 4105: 4099: 4098: 4096: 4094: 4074: 4068: 4067: 4065: 4063: 4043: 4032: 4031: 4029: 4027: 4016:The Mozilla Blog 4008: 4002: 4001: 3999: 3997: 3982: 3976: 3975: 3973: 3971: 3951: 3945: 3944: 3942: 3940: 3924: 3918: 3917: 3915: 3913: 3891: 3882: 3881: 3847: 3841: 3840: 3838: 3836: 3821: 3815: 3814: 3809: 3807: 3791: 3785: 3784: 3779: 3777: 3761: 3755: 3754: 3752: 3750: 3731: 3725: 3724: 3722: 3720: 3700: 3694: 3693: 3691: 3689: 3669: 3663: 3662: 3660: 3658: 3639: 3633: 3632: 3614: 3608: 3607: 3591: 3578: 3572: 3571: 3569: 3567: 3552: 3546: 3545: 3543: 3541: 3526: 3520: 3519: 3507: 3501: 3500: 3498: 3496: 3476: 3470: 3469: 3459: 3433: 3409: 3400: 3399: 3397: 3395: 3389: 3374: 3364: 3338: 3329: 3320: 3295: 3289: 3288: 3286: 3271: 3265: 3264: 3246: 3214: 3208: 3207: 3205: 3203: 3184: 3178: 3177: 3175: 3173: 3153: 3147: 3146: 3144: 3142: 3122: 3116: 3115: 3113: 3111: 3091: 3082: 3081: 3071: 3061: 3029: 3020: 3019: 3017: 3015: 2995: 2989: 2988: 2986: 2984: 2968: 2962: 2961: 2943: 2911: 2905: 2904: 2902: 2900: 2880: 2865: 2864: 2862: 2860: 2851:. May 16, 2011. 2841: 2832: 2831: 2815: 2809: 2808: 2806: 2778: 2772: 2771: 2769: 2745: 2739: 2738: 2736: 2734: 2694: 2688: 2687: 2685: 2675: 2651: 2645: 2644: 2639: 2637: 2621: 2615: 2614: 2598: 2589: 2588: 2570: 2564: 2563: 2561: 2559: 2545: 2539: 2538: 2520: 2488: 2482: 2481: 2463: 2439: 2433: 2432: 2430: 2402: 2396: 2395: 2385: 2367: 2335: 2329: 2328: 2326: 2324: 2310: 2301: 2300: 2298: 2296: 2277: 2264: 2258: 2257: 2255: 2253: 2231: 2225: 2224: 2222: 2220: 2198: 2192: 2191: 2189: 2187: 2167: 2161: 2160: 2158: 2156: 2138: 2132: 2131: 2129: 2127: 2107: 2098: 2097: 2092: 2090: 2070: 2064: 2063: 2027: 2021: 2020: 2018: 2016: 2010: 2003: 1994: 1988: 1987: 1985: 1983: 1963: 1954: 1953: 1947: 1945: 1926: 1920: 1919: 1914: 1912: 1892: 1883: 1882: 1877: 1875: 1856: 1850: 1849: 1847: 1845: 1823: 1817: 1816: 1814: 1812: 1796: 1790: 1789: 1787: 1769: 1745: 1739: 1738: 1736: 1734: 1719: 1713: 1712: 1710: 1708: 1680: 1674: 1673: 1668: 1666: 1646: 1635: 1634: 1632: 1630: 1611: 1600: 1599: 1563: 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5700:Jihadunspun.com 5686: 5667: 5592: 5568:New World Order 5536:Genocide denial 5507: 5492: 5441: 5426: 5348:Memetic warfare 5138: 5127: 5118: 5080: 5019: 4984: 4949: 4844: 4842: 4810: 4808:Further reading 4805: 4804: 4794: 4792: 4783: 4782: 4775: 4765: 4763: 4748: 4744: 4734: 4732: 4719: 4718: 4714: 4685:Current Biology 4677: 4670: 4660: 4658: 4641: 4637: 4627: 4625: 4610: 4606: 4551: 4547: 4537: 4535: 4520: 4516: 4463: 4459: 4428: 4424: 4414: 4412: 4399: 4398: 4394: 4387: 4373: 4369: 4359: 4357: 4342: 4338: 4328: 4326: 4313: 4312: 4308: 4298: 4296: 4281: 4277: 4256:(22): 2618–24. 4245: 4241: 4231: 4229: 4214: 4207: 4197: 4195: 4180: 4173: 4163: 4161: 4148: 4147: 4143: 4106: 4102: 4092: 4090: 4075: 4071: 4061: 4059: 4044: 4035: 4025: 4023: 4010: 4009: 4005: 3995: 3993: 3984: 3983: 3979: 3969: 3967: 3952: 3948: 3938: 3936: 3925: 3921: 3911: 3909: 3892: 3885: 3870: 3848: 3844: 3834: 3832: 3823: 3822: 3818: 3805: 3803: 3792: 3788: 3775: 3773: 3762: 3758: 3748: 3746: 3733: 3732: 3728: 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2185: 2183: 2168: 2164: 2154: 2152: 2139: 2135: 2125: 2123: 2108: 2101: 2088: 2086: 2079:Chicago Tribune 2071: 2067: 2028: 2024: 2014: 2012: 2008: 2001: 1995: 1991: 1981: 1979: 1964: 1957: 1943: 1941: 1928: 1927: 1923: 1910: 1908: 1901:Huffington Post 1893: 1886: 1873: 1871: 1858: 1857: 1853: 1843: 1841: 1824: 1820: 1810: 1808: 1797: 1793: 1746: 1742: 1732: 1730: 1721: 1720: 1716: 1706: 1704: 1697: 1681: 1677: 1664: 1662: 1655:Huffington Post 1647: 1638: 1628: 1626: 1613: 1612: 1603: 1564: 1555: 1510: 1501: 1488: 1486: 1471: 1467: 1454: 1452: 1437: 1433: 1420: 1418: 1403: 1396: 1381:10.1145/3055153 1365: 1358: 1348: 1346: 1331: 1322: 1308: 1306: 1291: 1282: 1272: 1270: 1255: 1236: 1222: 1220: 1205: 1196: 1181: 1159: 1155: 1142: 1140: 1125: 1112: 1077: 1073: 1063: 1061: 1046: 1042: 1037:Wayback Machine 1027: 1023: 992: 988: 982:Wayback Machine 972: 968: 963: 958: 957: 934: 930: 925: 920: 804:Internet portal 802: 795: 792: 780: 726:Mark Zuckerberg 691: 649: 570: 565: 563:Countermeasures 555:voted the word 459: 403: 388:Washington Post 352: 318: 316:Media reactions 313: 257: 251: 218: 208: 200:Eli Pariser in 199: 112: 24: 17: 12: 11: 5: 7150: 7140: 7139: 7134: 7129: 7127:Public opinion 7124: 7119: 7114: 7109: 7104: 7099: 7082: 7081: 7079: 7078: 7073: 7068: 7067: 7066: 7056: 7051: 7046: 7041: 7036: 7031: 7026: 7021: 7016: 7011: 7006: 7001: 6996: 6995: 6994: 6989: 6979: 6973: 6971: 6970:Related topics 6967: 6966: 6964: 6963: 6962: 6961: 6956: 6951: 6941: 6936: 6931: 6926: 6921: 6920: 6919: 6914: 6904: 6899: 6898: 6897: 6886: 6884: 6877:Digital divide 6873: 6872: 6870: 6869: 6864: 6859: 6854: 6849: 6844: 6839: 6838: 6837: 6832: 6822: 6817: 6812: 6807: 6801: 6799: 6792:Cognitive bias 6788: 6787: 6785: 6784: 6782:Sticky content 6779: 6778: 6777: 6772: 6770:Binge-watching 6762: 6757: 6752: 6747: 6742: 6737: 6732: 6727: 6726: 6725: 6720: 6715: 6710: 6700: 6695: 6694: 6693: 6686:Digital zombie 6683: 6682: 6681: 6671: 6666: 6661: 6659:Attention span 6656: 6651: 6646: 6640: 6638: 6632: 6631: 6629: 6628: 6623: 6618: 6613: 6612: 6611: 6604:Sensationalism 6601: 6596: 6591: 6590: 6589: 6584: 6579: 6569: 6564: 6563: 6562: 6557: 6552: 6550:Junk food news 6547: 6537: 6532: 6526: 6524: 6520: 6519: 6517: 6516: 6511: 6506: 6501: 6500: 6499: 6494: 6489: 6479: 6474: 6468: 6465: 6464: 6453: 6452: 6445: 6438: 6430: 6421: 6420: 6417: 6416: 6414: 6413: 6408: 6403: 6398: 6393: 6388: 6383: 6378: 6373: 6368: 6363: 6358: 6353: 6348: 6343: 6338: 6337: 6336: 6325: 6322: 6321: 6311: 6310: 6307: 6306: 6303: 6302: 6300: 6299: 6294: 6288: 6286: 6282: 6281: 6276: 6274: 6270: 6269: 6267: 6266: 6261: 6256: 6251: 6246: 6241: 6236: 6231: 6229:Habbush letter 6226: 6221: 6216: 6215: 6214: 6204: 6199: 6198: 6197: 6192: 6187: 6182: 6172: 6167: 6161: 6159: 6155: 6154: 6152: 6151: 6146: 6141: 6136: 6128: 6123: 6118: 6113: 6111:Bell Pottinger 6107: 6105: 6104:United Kingdom 6101: 6100: 6098: 6097: 6092: 6087: 6081: 6079: 6075: 6074: 6069: 6067: 6063: 6062: 6059: 6058: 6056: 6055: 6050: 6045: 6040: 6035: 6034: 6033: 6028: 6023: 6015: 6014: 6013: 6003: 6002: 6001: 5996: 5985: 5983: 5977: 5976: 5974: 5973: 5968: 5963: 5958: 5953: 5948: 5943: 5938: 5932: 5930: 5921: 5912: 5911: 5909: 5908: 5903: 5898: 5887: 5885: 5881: 5880: 5875: 5873: 5869: 5868: 5863: 5861: 5857: 5856: 5851: 5849: 5845: 5844: 5839: 5837: 5833: 5832: 5830: 5829: 5824: 5819: 5814: 5808: 5806: 5802: 5801: 5799: 5798: 5793: 5788: 5782: 5780: 5776: 5775: 5770: 5768: 5767:Czechoslovakia 5764: 5763: 5761: 5760: 5753: 5748: 5747: 5746: 5741: 5739:PLA Unit 61398 5736: 5731: 5726: 5721: 5710: 5708: 5704: 5703: 5698: 5696: 5688: 5687: 5677: 5676: 5673: 5672: 5669: 5668: 5666: 5665: 5660: 5659: 5658: 5653: 5648: 5638: 5633: 5628: 5623: 5618: 5617: 5616: 5614:by governments 5606: 5600: 5598: 5591: 5590: 5585: 5580: 5575: 5570: 5565: 5560: 5555: 5550: 5545: 5544: 5543: 5533: 5528: 5523: 5518: 5512: 5509: 5508: 5498: 5497: 5494: 5493: 5491: 5490: 5483: 5476: 5469: 5462: 5455: 5451:Disinformation 5446: 5443: 5442: 5432: 5431: 5428: 5427: 5425: 5424: 5419: 5414: 5409: 5404: 5399: 5394: 5389: 5384: 5379: 5378: 5377: 5372: 5367: 5357: 5356: 5355: 5350: 5340: 5335: 5330: 5325: 5320: 5315: 5310: 5305: 5300: 5295: 5290: 5285: 5280: 5275: 5270: 5265: 5260: 5255: 5254: 5253: 5243: 5242: 5241: 5236: 5231: 5221: 5216: 5211: 5206: 5201: 5196: 5191: 5181: 5180: 5179: 5172:Cognitive bias 5169: 5164: 5162:Cherry picking 5159: 5154: 5149: 5143: 5140: 5139: 5129: 5128: 5125:misinformation 5121:Disinformation 5117: 5116: 5109: 5102: 5094: 5088: 5087: 5079: 5078:External links 5076: 5075: 5074: 5046:(3): 298–301. 5031: 5017: 4996: 4982: 4961: 4947: 4926: 4906:(1): 210–230. 4891: 4879:(4): 249–265. 4864: 4851: 4829: 4813:Pariser, Eli. 4809: 4806: 4803: 4802: 4773: 4742: 4712: 4668: 4635: 4604: 4565:(3): 554–559. 4545: 4514: 4457: 4438:(2): 151–166. 4422: 4392: 4385: 4367: 4336: 4306: 4275: 4239: 4205: 4188:Marketing Land 4171: 4141: 4120:(3): 330–343. 4100: 4069: 4033: 4003: 3977: 3946: 3919: 3883: 3868: 3854:. p. 95. 3842: 3816: 3786: 3756: 3726: 3695: 3678:Marketing Land 3664: 3634: 3627: 3609: 3602: 3573: 3547: 3521: 3502: 3471: 3424:(11): 190868. 3401: 3321: 3290: 3266: 3209: 3179: 3148: 3117: 3083: 3021: 3004:Slate Magazine 2990: 2963: 2906: 2866: 2833: 2810: 2773: 2740: 2709:(3): 637–654. 2689: 2646: 2616: 2590: 2583: 2565: 2540: 2483: 2434: 2413:(2): 317–332. 2397: 2330: 2302: 2288: 2259: 2226: 2193: 2162: 2133: 2099: 2065: 2022: 1989: 1955: 1921: 1884: 1851: 1818: 1791: 1740: 1714: 1695: 1675: 1636: 1601: 1574:(2): 253–258. 1553: 1524:(3): 298–301. 1499: 1465: 1431: 1394: 1356: 1320: 1280: 1234: 1194: 1179: 1153: 1110: 1071: 1040: 1021: 1002:(3): 209–227. 986: 965: 964: 962: 959: 956: 955: 927: 926: 924: 921: 919: 918: 913: 906: 900: 895: 890: 885: 880: 875: 870: 865: 860: 855: 850: 845: 840: 835: 830: 825: 820: 815: 809: 808: 807: 791: 788: 779: 776: 745:Social sorting 695:cloud services 690: 687: 648: 645: 578:social capital 569: 568:By individuals 566: 564: 561: 458: 455: 409:that analyzed 402: 399: 317: 314: 312: 309: 250: 247: 217: 214: 197: 111: 108: 15: 9: 6: 4: 3: 2: 7149: 7138: 7135: 7133: 7130: 7128: 7125: 7123: 7120: 7118: 7115: 7113: 7110: 7108: 7105: 7103: 7100: 7098: 7095: 7094: 7092: 7077: 7074: 7072: 7069: 7065: 7062: 7061: 7060: 7057: 7055: 7052: 7050: 7047: 7045: 7042: 7040: 7037: 7035: 7032: 7030: 7027: 7025: 7022: 7020: 7017: 7015: 7012: 7010: 7007: 7005: 7002: 7000: 6997: 6993: 6990: 6988: 6985: 6984: 6983: 6980: 6978: 6977:Computer rage 6975: 6974: 6972: 6968: 6960: 6957: 6955: 6952: 6950: 6949:United States 6947: 6946: 6945: 6942: 6940: 6937: 6935: 6932: 6930: 6927: 6925: 6924:Filter bubble 6922: 6918: 6917:United States 6915: 6913: 6910: 6909: 6908: 6905: 6903: 6900: 6896: 6893: 6892: 6891: 6888: 6887: 6885: 6883: 6878: 6874: 6868: 6865: 6863: 6860: 6858: 6855: 6853: 6852:Peer pressure 6850: 6848: 6845: 6843: 6840: 6836: 6833: 6831: 6828: 6827: 6826: 6823: 6821: 6818: 6816: 6813: 6811: 6808: 6806: 6803: 6802: 6800: 6798: 6793: 6789: 6783: 6780: 6776: 6773: 6771: 6768: 6767: 6766: 6763: 6761: 6758: 6756: 6753: 6751: 6748: 6746: 6743: 6741: 6738: 6736: 6733: 6731: 6728: 6724: 6721: 6719: 6716: 6714: 6711: 6709: 6706: 6705: 6704: 6701: 6699: 6698:Doomscrolling 6696: 6692: 6689: 6688: 6687: 6684: 6680: 6677: 6676: 6675: 6672: 6670: 6667: 6665: 6662: 6660: 6657: 6655: 6652: 6650: 6647: 6645: 6642: 6641: 6639: 6637: 6633: 6627: 6624: 6622: 6619: 6617: 6614: 6610: 6607: 6606: 6605: 6602: 6600: 6597: 6595: 6592: 6588: 6585: 6583: 6580: 6578: 6575: 6574: 6573: 6570: 6568: 6565: 6561: 6558: 6556: 6553: 6551: 6548: 6546: 6543: 6542: 6541: 6538: 6536: 6533: 6531: 6528: 6527: 6525: 6521: 6515: 6512: 6510: 6509:Media studies 6507: 6505: 6502: 6498: 6495: 6493: 6490: 6488: 6485: 6484: 6483: 6480: 6478: 6475: 6473: 6470: 6469: 6466: 6462: 6461:human factors 6458: 6451: 6446: 6444: 6439: 6437: 6432: 6431: 6428: 6412: 6409: 6407: 6404: 6402: 6399: 6397: 6394: 6392: 6389: 6387: 6384: 6382: 6379: 6377: 6374: 6372: 6371:FactCheck.org 6369: 6367: 6364: 6362: 6359: 6357: 6354: 6352: 6349: 6347: 6344: 6342: 6339: 6335: 6332: 6331: 6330: 6329:Fact-checking 6327: 6326: 6323: 6316: 6312: 6298: 6295: 6293: 6290: 6289: 6287: 6283: 6279: 6275: 6271: 6265: 6262: 6260: 6257: 6255: 6252: 6250: 6247: 6245: 6242: 6240: 6237: 6235: 6232: 6230: 6227: 6225: 6222: 6220: 6217: 6213: 6210: 6209: 6208: 6205: 6203: 6200: 6196: 6193: 6191: 6188: 6186: 6183: 6181: 6178: 6177: 6176: 6173: 6171: 6168: 6166: 6163: 6162: 6160: 6158:United States 6156: 6150: 6147: 6145: 6142: 6140: 6137: 6135: 6133: 6129: 6127: 6124: 6122: 6119: 6117: 6114: 6112: 6109: 6108: 6106: 6102: 6096: 6093: 6091: 6088: 6086: 6083: 6082: 6080: 6076: 6072: 6068: 6064: 6054: 6051: 6049: 6046: 6044: 6041: 6039: 6036: 6032: 6029: 6027: 6024: 6022: 6019: 6018: 6016: 6012: 6009: 6008: 6007: 6004: 6000: 5997: 5995: 5992: 5991: 5990: 5987: 5986: 5984: 5982: 5978: 5972: 5969: 5967: 5964: 5962: 5959: 5957: 5954: 5952: 5949: 5947: 5944: 5942: 5939: 5937: 5934: 5933: 5931: 5929: 5925: 5922: 5917: 5913: 5907: 5904: 5902: 5899: 5896: 5892: 5889: 5888: 5886: 5882: 5878: 5874: 5870: 5866: 5862: 5858: 5854: 5850: 5846: 5842: 5838: 5834: 5828: 5825: 5823: 5820: 5818: 5815: 5813: 5810: 5809: 5807: 5803: 5797: 5794: 5792: 5789: 5787: 5784: 5783: 5781: 5777: 5773: 5769: 5765: 5759: 5758: 5754: 5752: 5749: 5745: 5742: 5740: 5737: 5735: 5732: 5730: 5727: 5725: 5722: 5720: 5719:50 Cent Party 5717: 5716: 5715: 5712: 5711: 5709: 5705: 5701: 5697: 5693: 5689: 5682: 5678: 5664: 5661: 5657: 5654: 5652: 5649: 5647: 5644: 5643: 5642: 5639: 5637: 5634: 5632: 5629: 5627: 5624: 5622: 5619: 5615: 5612: 5611: 5610: 5607: 5605: 5602: 5601: 5599: 5595: 5589: 5586: 5584: 5581: 5579: 5576: 5574: 5571: 5569: 5566: 5564: 5561: 5559: 5556: 5554: 5551: 5549: 5546: 5542: 5539: 5538: 5537: 5534: 5532: 5529: 5527: 5524: 5522: 5519: 5517: 5514: 5513: 5510: 5503: 5499: 5489: 5488: 5484: 5482: 5481: 5477: 5475: 5474: 5470: 5468: 5467: 5463: 5461: 5460: 5456: 5454: 5452: 5448: 5447: 5444: 5437: 5433: 5423: 5420: 5418: 5415: 5413: 5410: 5408: 5405: 5403: 5400: 5398: 5395: 5393: 5390: 5388: 5385: 5383: 5380: 5376: 5373: 5371: 5368: 5366: 5363: 5362: 5361: 5358: 5354: 5351: 5349: 5346: 5345: 5344: 5341: 5339: 5336: 5334: 5331: 5329: 5326: 5324: 5323:Media culture 5321: 5319: 5316: 5314: 5311: 5309: 5306: 5304: 5301: 5299: 5296: 5294: 5291: 5289: 5286: 5284: 5281: 5279: 5276: 5274: 5271: 5269: 5266: 5264: 5263:False dilemma 5261: 5259: 5256: 5252: 5249: 5248: 5247: 5244: 5240: 5237: 5235: 5232: 5230: 5227: 5226: 5225: 5222: 5220: 5217: 5215: 5212: 5210: 5207: 5205: 5202: 5200: 5197: 5195: 5192: 5189: 5185: 5182: 5178: 5175: 5174: 5173: 5170: 5168: 5165: 5163: 5160: 5158: 5155: 5153: 5150: 5148: 5145: 5144: 5141: 5134: 5130: 5126: 5122: 5115: 5110: 5108: 5103: 5101: 5096: 5095: 5092: 5085: 5082: 5081: 5071: 5067: 5062: 5057: 5053: 5049: 5045: 5041: 5037: 5032: 5028: 5024: 5020: 5018:9781450318990 5014: 5010: 5006: 5002: 4997: 4993: 4989: 4985: 4983:9781450313322 4979: 4975: 4971: 4967: 4962: 4958: 4954: 4950: 4948:9781450327442 4944: 4940: 4936: 4932: 4927: 4923: 4919: 4914: 4909: 4905: 4901: 4897: 4892: 4887: 4882: 4878: 4874: 4870: 4865: 4861: 4857: 4852: 4841: 4840: 4835: 4830: 4828: 4824: 4820: 4819:Penguin Press 4816: 4812: 4811: 4790: 4786: 4780: 4778: 4761: 4757: 4753: 4746: 4730: 4726: 4725:Farnam Street 4722: 4716: 4707: 4702: 4698: 4694: 4690: 4686: 4682: 4675: 4673: 4656: 4652: 4651: 4646: 4639: 4623: 4619: 4615: 4608: 4600: 4596: 4591: 4586: 4581: 4576: 4572: 4568: 4564: 4560: 4556: 4549: 4533: 4529: 4525: 4518: 4510: 4506: 4501: 4496: 4492: 4488: 4484: 4480: 4476: 4472: 4468: 4461: 4453: 4449: 4445: 4441: 4437: 4433: 4426: 4410: 4406: 4405:The Economist 4402: 4396: 4388: 4382: 4378: 4371: 4355: 4351: 4347: 4340: 4324: 4320: 4316: 4310: 4294: 4290: 4286: 4279: 4271: 4267: 4263: 4259: 4255: 4251: 4243: 4227: 4223: 4219: 4212: 4210: 4193: 4189: 4185: 4178: 4176: 4159: 4155: 4151: 4145: 4137: 4133: 4128: 4123: 4119: 4115: 4111: 4104: 4088: 4084: 4080: 4073: 4057: 4053: 4049: 4042: 4040: 4038: 4021: 4017: 4013: 4007: 3991: 3987: 3981: 3965: 3961: 3957: 3950: 3934: 3930: 3923: 3912:September 24, 3907: 3903: 3902: 3897: 3890: 3888: 3879: 3875: 3871: 3865: 3861: 3857: 3853: 3846: 3830: 3826: 3820: 3813: 3801: 3797: 3790: 3783: 3771: 3767: 3760: 3744: 3740: 3736: 3730: 3714: 3710: 3706: 3699: 3683: 3679: 3675: 3668: 3652: 3648: 3644: 3638: 3630: 3628:9780199243679 3624: 3620: 3613: 3605: 3599: 3595: 3590: 3589: 3583: 3577: 3561: 3557: 3551: 3535: 3531: 3525: 3517: 3513: 3506: 3490: 3486: 3482: 3475: 3467: 3463: 3458: 3453: 3449: 3445: 3441: 3437: 3432: 3427: 3423: 3419: 3415: 3408: 3406: 3386: 3382: 3378: 3373: 3368: 3363: 3358: 3354: 3350: 3346: 3342: 3335: 3328: 3326: 3319: 3315: 3312: 3308: 3304: 3301: 3294: 3285: 3280: 3277: 3270: 3262: 3258: 3254: 3250: 3245: 3240: 3236: 3232: 3228: 3224: 3220: 3213: 3197: 3193: 3189: 3183: 3167: 3163: 3159: 3152: 3136: 3132: 3128: 3121: 3105: 3101: 3097: 3090: 3088: 3079: 3075: 3070: 3065: 3060: 3055: 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