scispace - formally typeset
Open accessJournal ArticleDOI: 10.1073/PNAS.2023301118

The echo chamber effect on social media

02 Mar 2021-Proceedings of the National Academy of Sciences of the United States of America (National Academy of Sciences)-Vol. 118, Iss: 9
Abstract: Social media may limit the exposure to diverse perspectives and favor the formation of groups of like-minded users framing and reinforcing a shared narrative, that is, echo chambers. However, the interaction paradigms among users and feed algorithms greatly vary across social media platforms. This paper explores the key differences between the main social media platforms and how they are likely to influence information spreading and echo chambers’ formation. We perform a comparative analysis of more than 100 million pieces of content concerning several controversial topics (e.g., gun control, vaccination, abortion) from Gab, Facebook, Reddit, and Twitter. We quantify echo chambers over social media by two main ingredients: 1) homophily in the interaction networks and 2) bias in the information diffusion toward like-minded peers. Our results show that the aggregation of users in homophilic clusters dominate online interactions on Facebook and Twitter. We conclude the paper by directly comparing news consumption on Facebook and Reddit, finding higher segregation on Facebook.

... read more

Topics: Social media (63%), Homophily (52%)

56 results found

Open accessJournal ArticleDOI: 10.1073/PNAS.2024292118
Abstract: There has been growing concern about the role social media plays in political polarization. We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts and US congressional members (n = 2,730,215), we found that posts about the political out-group were shared or retweeted about twice as often as posts about the in-group. Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%. Out-group language consistently emerged as the strongest predictor of shares and retweets: the average effect size of out-group language was about 4.8 times as strong as that of negative affect language and about 6.7 times as strong as that of moral-emotional language—both established predictors of social media engagement. Language about the out-group was a very strong predictor of “angry” reactions (the most popular reactions across all datasets), and language about the in-group was a strong predictor of “love” reactions, reflecting in-group favoritism and out-group derogation. This out-group effect was not moderated by political orientation or social media platform, but stronger effects were found among political leaders than among news media accounts. In sum, out-group language is the strongest predictor of social media engagement across all relevant predictors measured, suggesting that social media may be creating perverse incentives for content expressing out-group animosity.

... read more

Topics: Social media (58%), News media (57%), Social identity theory (53%) ... show more

8 Citations

Open accessJournal ArticleDOI: 10.1145/3479556
Abstract: YouTube is by far the largest host of user-generated video content worldwide. Alas, the platform also hosts inappropriate, toxic, and hateful content. One community that has often been linked to sharing and publishing hateful and misogynistic content is the so-called Involuntary Celibates (Incels), a loosely defined movement ostensibly focusing on men's issues. In this paper, we set out to analyze the Incel community on YouTube by focusing on this community's evolution over the last decade and understanding whether YouTube's recommendation algorithm steers users towards Incel-related videos. We collect videos shared on Incel communities within Reddit and perform a data-driven characterization of the content posted on YouTube. Among other things, we find that the Incel community on YouTube is getting traction and that during the last decade, the number of Incel-related videos and comments rose substantially. We also find that users have a 6.3% of being suggested an Incel-related video by YouTube's recommendation algorithm within five hops when starting from a non-Incel-related video. Overall, our findings paint an alarming picture of online radicalization: not only Incel activity is increasing over time, but platforms may also play an active role in steering users towards such extreme content.

... read more

5 Citations

Open accessJournal ArticleDOI: 10.3390/APP11125390
10 Jun 2021-Applied Sciences
Abstract: In a digital environment, the term echo chamber refers to an alarming phenomenon in which beliefs are amplified or reinforced by communication repetition inside a closed system and insulated from rebuttal. Up to date, a formal definition, as well as a platform-independent approach for its detection, is still lacking. This paper proposes a general framework to identify echo chambers on online social networks built on top of features they commonly share. Our approach is based on a four-step pipeline that involves (i) the identification of a controversial issue; (ii) the inference of users’ ideology on the controversy; (iii) the construction of users’ debate network; and (iv) the detection of homogeneous meso-scale communities. We further apply our framework in a detailed case study on Reddit, covering the first two and a half years of Donald Trump’s presidency. Our main purpose is to assess the existence of Pro-Trump and Anti-Trump echo chambers among three sociopolitical issues, as well as to analyze their stability and consistency over time. Even if users appear strongly polarized with respect to their ideology, most tend not to insulate themselves in echo chambers. However, the found polarized communities were proven to be definitely stable over time.

... read more

Topics: Echo (computing) (52%)

2 Citations

Open accessPosted Content
Abstract: Dialogue models trained on human conversations inadvertently learn to generate toxic responses. In addition to producing explicitly offensive utterances, these models can also implicitly insult a group or individual by aligning themselves with an offensive statement. To better understand the dynamics of contextually offensive language, we investigate the stance of dialogue model responses in offensive Reddit conversations. Specifically, we create ToxiChat, a crowd-annotated dataset of 2,000 Reddit threads and model responses labeled with offensive language and stance. Our analysis reveals that 42% of human responses agree with toxic comments, whereas only 13% agree with safe comments. This undesirable behavior is learned by neural dialogue models, such as DialoGPT, which we show are two times more likely to agree with offensive comments. To enable automatic detection of offensive language, we fine-tuned transformer-based classifiers on ToxiChat that achieve 0.71 F1 for offensive labels and 0.53 Macro-F1 for stance labels. Finally, we quantify the effectiveness of controllable text generation (CTG) methods to mitigate the tendency of neural dialogue models to agree with offensive comments. Compared to the baseline, our best CTG model achieves a 19% reduction in agreement with offensive comments and produces 29% fewer offensive replies. Our work highlights the need for further efforts to characterize and analyze inappropriate behavior in dialogue models, in order to help make them safer. Our code and corpus are available at this https URL .

... read more

Topics: Offensive (62%)

2 Citations

Open accessPosted ContentDOI: 10.31234/OSF.IO/UCTXA
21 May 2021-
Abstract: Preferential learning from like-minded others can help individuals acquire adaptive knowledge and socially appropriate behaviour, but it can also reinforce echo chambers and fuel polarization. Ingroup bias is well-documented in the social transmission of opinions, attitudes, and values. However, important questions about its role in the integration of social information when forming factual beliefs are outstanding. We present a naturalistic yet controlled experiment showing that social information is most impactful when provided by ingroup rather than outgroup sources. Participants predicted the 2020 US elections by state and could adjust their predictions after observing the prediction of a Democrat or a Republican. Adjustments were largest when observing fellow-partisans, and when social information favoured the participants’ party. Exploratory analyses reveal that these partisan biases are driven by Republican participants. Our findings help understand the variation of social information use along political orientations and its consequences for belief polarization in increasingly fragmented populations.

... read more

2 Citations


51 results found

Open accessJournal ArticleDOI: 10.1088/1742-5468/2008/10/P10008
Abstract: We propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection methods in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2 million customers and by analysing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad hoc modular networks.

... read more

Topics: Modularity (networks) (67%), Clique percolation method (62%), Girvan–Newman algorithm (57%) ... show more

11,078 Citations

Open accessJournal ArticleDOI: 10.1037/1089-2680.2.2.175
Raymond S. Nickerson1Institutions (1)
Abstract: Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a h...

... read more

Topics: Confirmation bias (59%), Response bias (54%)

4,417 Citations

Journal ArticleDOI: 10.1080/01621459.1974.10480137
Morris H. DeGroot1Institutions (1)
Abstract: Consider a group of individuals who must act together as a team or committee, and suppose that each individual in the group has his own subjective probability distribution for the unknown value of some parameter. A model is presented which describes how the group might reach agreement on a common subjective probability distribution for the parameter by pooling their individual opinions. The process leading to the consensus is explicitly described and the common distribution that is reached is explicitly determined. The model can also be applied to problems of reaching a consensus when the opinion of each member of the group is represented simply as a point estimate of the parameter rather than as a probability distribution.

... read more

3,034 Citations

Open accessJournal ArticleDOI: 10.1126/SCIENCE.AAP9559
Soroush Vosoughi1, Deb Roy1, Sinan Aral1Institutions (1)
09 Mar 2018-Science
Abstract: We investigated the differential diffusion of all of the verified true and false news stories distributed on Twitter from 2006 to 2017. The data comprise ~126,000 stories tweeted by ~3 million people more than 4.5 million times. We classified news as true or false using information from six independent fact-checking organizations that exhibited 95 to 98% agreement on the classifications. Falsehood diffused significantly farther, faster, deeper, and more broadly than the truth in all categories of information, and the effects were more pronounced for false political news than for false news about terrorism, natural disasters, science, urban legends, or financial information. We found that false news was more novel than true news, which suggests that people were more likely to share novel information. Whereas false stories inspired fear, disgust, and surprise in replies, true stories inspired anticipation, sadness, joy, and trust. Contrary to conventional wisdom, robots accelerated the spread of true and false news at the same rate, implying that false news spreads more than the truth because humans, not robots, are more likely to spread it.

... read more

Topics: Disinformation (51%)

2,621 Citations

Open accessBook
01 Jan 1960-
Abstract: PrefaceNATURE OF THE BOOK This book attempts to collate and integrate thenfindings of published research, and some provocative conjecture,nregarding certain social and psychological effects of mass communicationMore specifically, the book is concerned with two major areasnof such effect Part I deals with mass communication as an agentnof persuasion and attempts to cite its known capabilities and limitationsnin that regard Part II deals with the effects of specific kindsnof media content which have been alleged to produce socially andnpsychologically important consequences An introductory chapter,nwhich is largely subjective, discusses the current state ofnknowledge of the effects of mass communication in general andnproposes a primitive theoretical scheme which is further discussed at various other explicitly labeled places in the book andnin the conclusion Except for the introduction and conclusion,nthe entire work is primarily a collection of the findings of othersThe book at times draws heavily upon an earlier work by thensame author (Klapper, 1949) The present volume, however, isnby no means a mere up-dating of the earlier one It differs from thenearlier work in its inclusion and discussion of the proposed theoreticalnscheme, in its far greater concern with extra-communicationnconditions which influence the effect of communications, and innthe areas of effect which are discussed Of the five topics discussednin the earlier volume, three have been retained and two of thesenare treated in much greater detail, and two have been omittednThree topics not treated in the earlier volume are here accordedna chapter eachLITERATURE SURVEYEDThe source material for this book consisted mainly of the vastnarray of learned and semi-leamed journals and of relevant booksnTraditional techniques of library research were employed in cullingnthis literature Journals of abstracts, bibliographies, and worksnknown to the author were used as starting points; the works citedncontained bibliographies and references which led to additionalnmaterial; and this snowballing was continued until the returnsnbecame so slight that it was clearly unprofitable to continueThis process led to the identification and investigation of overn1000 studies, essays, and reports More than 270 of these, which contributedndirectly to the present volume, are cited in the bibliographynThe others were found to be either wholly irrelevant tonthe topics of the book, to be so methodologically culpable as to benuseless, or, in some cases, to provide only one more confirmationnof some highly specific finding or point of view that had beennwidely confirmed or better expressed in other cited worksThe primary object of the literature search was to locate allnpublished reports of disciplined social research dealing with effectsno f mass communication in certain specific areas However, several unpublished works have found their way into the text and thenbibliography These include occasional doctoral dissertationsnwhich have attained some recognition outside the departments innwhich they were written, and several reports issued in unpublishednform by academic, commercial, and government agenciesnNo attempt has been made, however, exhaustively to explore suchnsources of unpublished material; the almost limitless volume, thenfrequently privileged status, and, above all, the sheer difficulty ofntracking down and obtaining these little-known works renderednany attempt at exhaustive examination beyond the budgetary andnphysical capabilities of the present study The value to the researchn fraternity of a central clearing house or information centernfor such materials has often been noted; unless and until the conceptnis somehow implemented, knowledge of the materials, andnthus their potential usefulness, will remain severely limitednIt must also be noted that a considerable number of the citednworks are not reports of research at all, but rather present thenconsidered conjecture of reputable and acute thinkers In addition,narticles from popular sources (eg, Parents Magazine) arenoccasionally cited as evidence of popular concern about particularneffects of the mediaFinally, and perhaps most importantly, a considerable numbernof the cited research studies do not deal with mass communicationsnper se, but with laboratory approximations thereof or with somenform of interpersonal communication; they have been included asnsource material because their findings appear to be at least hypotheticallynapplicable to mass communication as welln n n n n n

... read more

1,571 Citations

No. of citations received by the Paper in previous years
Network Information
Related Papers (5)
Exposure to ideologically diverse news and opinion on Facebook05 Jun 2015, Science

Eytan Bakshy, Solomon Messing +2 more

The spread of true and false news online09 Mar 2018, Science

Soroush Vosoughi, Deb Roy +1 more

Birds of a Feather: Homophily in Social Networks01 Aug 2001, Review of Sociology

Miller McPherson, Lynn Smith-Lovin +1 more