Echo chambers in the age of misinformation

The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. Despite the enthusiastic rhetoric on the part of some that this process generates "collective intelligence", the WWW also allows the rapid dissemination of unsubstantiated conspiracy theories that often elicite rapid, large, but naive social responses such as the recent case of Jade Helm 15 -- where a simple military exercise turned out to be perceived as the beginning of the civil war in the US. We study how Facebook users consume information related to two different kinds of narrative: scientific and conspiracy news. We find that although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, the sizes of the spreading cascades differ. Homogeneity appears to be the primary driver for the diffusion of contents, but each echo chamber has its own cascade dynamics. To mimic these dynamics, we introduce a data-driven percolation model on signed networks.

[1]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[2]  P. Resnick,et al.  RumorLens: A System for Analyzing the Impact of Rumors and Corrections in Social Media , 2014 .

[3]  Michela Del Vicario,et al.  Viral Misinformation: The Role of Homophily and Polarization , 2014, WWW.

[4]  E. Loftus,et al.  Individual differences in false memory from misinformation: personality characteristics and their interactions with cognitive abilities , 2022 .

[5]  Lynne M. Reder,et al.  A theoretical review of the misinformation effect: Predictions from an activation-based memory model , 1998 .

[6]  Bin Gu,et al.  Research Note - The Allure of Homophily in Social Media: Evidence from Investor Responses on Virtual Communities , 2014, Inf. Syst. Res..

[7]  Wei Zhang,et al.  Knowledge-Based Trust: Estimating the Trustworthiness of Web Sources , 2015, Proc. VLDB Endow..

[8]  J. Byford.  Conspiracy Theories: A Critical Introduction , 2011 .

[9]  Henry L Roediger,et al.  Explorations in the social contagion of memory , 2002, Memory & cognition.

[10]  C. Betsch,et al.  Debunking vaccination myths: strong risk negations can increase perceived vaccination risks. , 2013, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[11]  Jacob Ratkiewicz,et al.  Detecting and Tracking Political Abuse in Social Media , 2011, ICWSM.

[12]  R. Kelly Garrett,et al.  Echo chambers online?: Politically motivated selective exposure among Internet news users , 2009, J. Comput. Mediat. Commun..

[13]  Qian Zhang,et al.  Collective attention in the age of (mis)information , 2014, Comput. Hum. Behav..

[14]  A. Koriat,et al.  Toward a psychology of memory accuracy. , 2000, Annual review of psychology.

[15]  Douglas Kellner,et al.  New Media and Internet Activism: From the ‘Battle of Seattle’ to Blogging , 2004, New Media Soc..

[16]  Elizabeth F. Loftus,et al.  Current Issues and Advances in Misinformation Research , 2011 .

[17]  Ravi Kumar,et al.  Dynamics of conversations , 2010, KDD.

[18]  Dragomir R. Radev,et al.  Rumor has it: Identifying Misinformation in Microblogs , 2011, EMNLP.

[19]  Ponnurangam Kumaraguru,et al.  TweetCred: Real-Time Credibility Assessment of Content on Twitter , 2014, SocInfo.

[20]  G. Fine,et al.  Rumor Mills: The Social Impact of Rumor and Legend , 2017 .

[21]  M. Hogg,et al.  Extremism and the psychology of uncertainty. , 2012 .

[22]  Antonio Scala,et al.  The economy of attention in the age of (mis)information , 2014, Journal of Trust Management.

[23]  C. Sunstein,et al.  Conspiracy Theories: Causes and Cures* , 2009 .

[24]  Guido Caldarelli,et al.  Opinion dynamics on interacting networks: media competition and social influence , 2014, Scientific Reports.

[25]  B. Nyhan,et al.  Effective Messages in Vaccine Promotion: A Randomized Trial , 2014, Pediatrics.

[26]  Jure Leskovec,et al.  Signed networks in social media , 2010, CHI.

[27]  N. Lee,et al.  Word of mouth communication within online communities: Conceptualizing the online social network , 2007 .

[28]  Walter Quattrociocchi,et al.  Opinions Manipulation: Media, Power and Gossip , 2011, Adv. Complex Syst..

[29]  Amal Abdullah AlMansour,et al.  A MODEL FOR RECALIBRATING CREDIBILITY IN DIFFERENT CONTEXTS AND LANGUAGES - A TWITTER CASE STUDY , 2014 .

[30]  Johan Bollen,et al.  Computational Fact Checking from Knowledge Networks , 2015, PloS one.

[31]  R. Kelly Garrett,et al.  The promise and peril of real-time corrections to political misperceptions , 2013, CSCW.

[32]  James Surowiecki.  The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations Doubleday Books. , 2004 .

[33]  Guido Caldarelli,et al.  Science vs Conspiracy: Collective Narratives in the Age of Misinformation , 2014, PloS one.

[34]  Rossano Schifanella,et al.  Friendship prediction and homophily in social media , 2012, TWEB.