research-article

Open access

NudgeCred: Supporting News Credibility Assessment on Social Media Through Nudges

Authors:

Md Momen Bhuiyan,

Michael Horning,

Tanushree MitraAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 5, Issue CSCW2

Article No.: 427, Pages 1 - 30

https://doi.org/10.1145/3479571

Published: 18 October 2021 Publication History

Abstract

Struggling to curb misinformation, social media platforms are experimenting with design interventions to enhance consumption of credible news on their platforms. Some of these interventions, such as the use of warning messages, are examples of nudges---a choice-preserving technique to steer behavior. Despite their application, we do not know whether nudges could steer people into making conscious news credibility judgments online and if they do, under what constraints. To answer, we combine nudge techniques with heuristic based information processing to design NudgeCred--a browser extension for Twitter. NudgeCred directs users' attention to two design cues: authority of a source and other users' collective opinion on a report by activating three design nudges---Reliable, Questionable, and Unreliable, each denoting particular levels of credibility for news tweets. In a controlled experiment, we found that NudgeCred significantly helped users (n=430) distinguish news tweets' credibility, unrestricted by three behavioral confounds---political ideology, political cynicism, and media skepticism. A five-day field deployment with twelve participants revealed that NudgeCred improved their recognition of news items and attention towards all of our nudges, particularly towards Questionable. Among other considerations, participants proposed that designers should incorporate heuristics that users' would trust. Our work informs nudge-based system design approaches for online media.

References

[1]

Alexander T Adams, Jean Costa, Malte F Jung, and Tanzeem Choudhury. 2015. Mindless computing: designing technologies to subtly influence behavior. In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. 719--730.

Digital Library

[2]

Gediminas Adomavicius, Jesse Bockstedt, Shawn Curley, and Jingjing Zhang. 2014. De-biasing user preference ratings in recommender systems. In RecSys 2014 Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2014). Citeseer, 2--9.

[3]

Hunt Allcott and Matthew Gentzkow. 2017. Social media and fake news in the 2016 election. Journal of Economic Perspectives, Vol. 31, 2 (2017), 211--36.

[4]

Mike Allen. 1991. Meta-analysis comparing the persuasiveness of one-sided and two-sided messages. Western Journal of Speech Communication, Vol. 55, 4 (1991), 390--404.

[5]

AP. 2018. Associated Press News Values and Principles. https://www.ap.org/about/news-values-and-principles/.

[6]

Mevan Babakar. 2018. Crowdsourced Factchecking: There is a role for crowdsourcing in factchecking but (so far) it's not factchecking. https://medium.com/@meandvan/crowdsourced-factchecking-4c5168ea5ac3.

[7]

Khaled Bachour, Jon Bird, Vaiva Kalnikaite, Yvonne Rogers, Nicolas Villar, and Stefan Kreitmayer. 2012. Fast and frugal shopping challenge. In CHI'12 Extended Abstracts on Human Factors in Computing Systems. ACM, 1459--1460.

Digital Library

[8]

Rebecca Balebako, Pedro G Leon, Hazim Almuhimedi, Patrick Gage Kelley, Jonathan Mugan, Alessandro Acquisti, Lorrie Faith Cranor, and Norman Sadeh. 2011. Nudging users towards privacy on mobile devices. In Proc. CHI 2011 Workshop on Persuasion, Nudge, Influence and Coercion. Citeseer, 193--201.

[9]

Meital Balmas. 2014. When fake news becomes real: Combined exposure to multiple news sources and political attitudes of inefficacy, alienation, and cynicism. Communication research, Vol. 41, 3 (2014), 430--454.

[10]

Joshua Becker, Ethan Porter, and Damon Centola. 2019. The wisdom of partisan crowds. Proceedings of the National Academy of Sciences, Vol. 116, 22 (2019), 10717--10722.

[11]

Md Momen Bhuiyan, Amy X Zhang, Connie Moon Sehat, and Tanushree Mitra. 2020. Investigating Differences in Crowdsourced News Credibility Assessment: Raters, Tasks, and Expert Criteria. arXiv preprint arXiv:2008.09533 (2020).

Digital Library

[12]

Md Momen Bhuiyan, Kexin Zhang, Kelsey Vick, Michael A Horning, and Tanushree Mitra. 2018. FeedReflect: A tool for nudging users to assess news credibility on twitter. In Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing. 205--208.

Digital Library

[13]

Oversight Board. 2020. Oversight Board | Independent Judgment. Transparency. Legitimacy. https://oversightboard.com/. (Accessed on 04/05/2021).

[14]

Ben Bolker. 2018. lme4 package | R Documentation. https://www. rdocumentation.org/packages/lme4/versions/1.1--18--1.

[15]

Toby Bolsen and James N Druckman. 2015. Counteracting the politicization of science. J. Commun., Vol. 65, 5 (2015), 745--769.

[16]

Marilynn B Brewer and William D Crano. 2000. Research design and issues of validity. Handbook of research methods in social and personality psychology (2000), 3--16.

[17]

Campbell Brown. 2019. Introducing Facebook News - About Facebook. https://about.fb.com/news/2019/10/introducing-facebook-news/. (Accessed on 09/11/2020).

[18]

Guido Buelow. 2019. Automation Plus Expert Journalism: How Full Fact is Fighting Misinformation - About Facebook. https://about.fb.com/news/2019/06/inside-feed-full-fact-interview/. (Accessed on 09/11/2020).

[19]

Julie G Bush, Hollyn M Johnson, and Colleen M Seifert. 1994. The implications of corrections: Then why did you mention it. (1994).

[20]

Joseph N Cappella and Kathleen Hall Jamieson. 1997. Spiral of cynicism: The press and the public good .Oxford University Press on Demand.

[21]

Ana Caraban, Evangelos Karapanos, Daniel Goncc alves, and Pedro Campos. 2019. 23 Ways to Nudge: A Review of Technology-Mediated Nudging in Human-Computer Interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, 503.

Digital Library

[22]

D Jasun Carr, Matthew Barnidge, Byung Gu Lee, and Stephanie Jean Tsang. 2014. Cynics and skeptics: Evaluating the credibility of mainstream and citizen journalism. J. Mass Commun. Q., Vol. 91, 3 (2014), 452--470.

[23]

Carlos Castillo, Marcelo Mendoza, and Barbara Poblete. 2011. Information credibility on twitter. In Proc. WWW. ACM, 675--684.

Digital Library

[24]

Mike Caulfield. 2017. Web literacy for student fact-checkers. (2017).

[25]

Shelly Chaiken. 1987. The heuristic model of persuasion. In Social influence: the ontario symposium, Vol. 5. Hillsdale, NJ: Lawrence Erlbaum, 3--39.

[26]

Xinran Chen, Sei-Ching Joanna Sin, Yin-Leng Theng, and Chei Sian Lee. 2015. Deterring the spread of misinformation on social network sites: A social cognitive theory-guided intervention. Proceedings of the Association for Information Science and Technology, Vol. 52, 1 (2015), 1--4.

[27]

Cision. 2017. Top 10 U.S. Daily Newspapers. https://www. cision.com/us/2017/09/top-10-u-s-daily-newspapers-2/.

[28]

Russell D Clark III and Anne Maass. 1988. The role of social categorization and perceived source credibility in minority influence. European Journal of Social Psychology, Vol. 18, 5 (1988), 381--394.

[29]

Devin Coldewey. 2016. Reddit overhauls upvote algorithm to thwart cheaters and show the site's true scale | TechCrunch. https://techcrunch.com/2016/12/06/reddit-overhauls-upvote-algorithm-to-thwart-cheaters-and-show-the-sites-true-scale/?guccounter=1. (Accessed on 01/03/2021).

[30]

John Cook, Stephan Lewandowsky, and Ullrich KH Ecker. 2017. Neutralizing misinformation through inoculation: Exposing misleading argumentation techniques reduces their influence. PloS one, Vol. 12, 5 (2017), e0175799.

[31]

Nicholas Diakopoulos, Munmun De Choudhury, and Mor Naaman. 2012. Finding and assessing social media information sources in the context of journalism. In Proc. CHI. ACM, 2451--2460.

Digital Library

[32]

Thomas Erickson and Wendy A Kellogg. 2000. Social translucence: an approach to designing systems that support social processes. ACM transactions on computer-human interaction (TOCHI), Vol. 7, 1 (2000), 59--83.

Digital Library

[33]

Jonathan St BT Evans. 2003. In two minds: dual-process accounts of reasoning. Trends in cognitive sciences, Vol. 7, 10 (2003), 454--459.

[34]

Facebook. 2019. How Facebook Has Prepared for the 2019 UK General Election - About Facebook. https://about.fb.com/news/2019/11/how-facebook-is-prepared-for-the-2019-uk-general-election/. (Accessed on 09/11/2020).

[35]

Maksym Gabielkov, Arthi Ramachandran, Augustin Chaintreau, and Arnaud Legout. 2016. Social clicks: What and who gets read on Twitter?. In Proceedings of the 2016 ACM SIGMETRICS international conference on measurement and modeling of computer science. 179--192.

Digital Library

[36]

R Kelly Garrett and Brian E Weeks. 2013. The promise and peril of real-time corrections to political misperceptions. In Proc. CSCW. ACM, 1047--1058.

[37]

Christine Geeng, Savanna Yee, and Franziska Roesner. 2020. Fake News on Facebook and Twitter: Investigating How People (Don't) Investigate. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1--14.

Digital Library

[38]

Catherine Grevet and Eric Gilbert. 2015. Piggyback prototyping: Using existing, large-scale social computing systems to prototype new ones. In Proc. CHI. ACM, 4047--4056.

Digital Library

[39]

Andrew Guess, Kevin Munger, Jonathan Nagler, and Joshua Tucker. 2019. How accurate are survey responses on social media and politics? Political Communication, Vol. 36, 2 (2019), 241--258.

[40]

Andrew M Guess, Michael Lerner, Benjamin Lyons, Jacob M Montgomery, Brendan Nyhan, Jason Reifler, and Neelanjan Sircar. 2020. A digital media literacy intervention increases discernment between mainstream and false news in the United States and India. Proceedings of the National Academy of Sciences, Vol. 117, 27 (2020), 15536--15545.

[41]

Aditi Gupta, Ponnurangam Kumaraguru, Carlos Castillo, and Patrick Meier. 2014. Tweetcred: Real-time credibility assessment of content on twitter. In International Conference on Social Informatics. Springer, 228--243.

[42]

David Halpern. 2016. Inside the nudge unit: How small changes can make a big difference .Random House.

[43]

Pelle Guldborg Hansen and Andreas Maaløe Jespersen. 2013. Nudge and the manipulation of choice: A framework for the responsible use of the nudge approach to behaviour change in public policy. European Journal of Risk Regulation, Vol. 4, 1 (2013), 3--28.

[44]

Karen Hao. 2021. He got Facebook hooked on AI. Now he can't fix its misinformation addiction | MIT Technology Review. https://www.technologyreview.com/2021/03/11/1020600/facebook-responsible-ai-misinformation/. (Accessed on 04/05/2021).

[45]

William Hart, Dolores Albarrac'in, Alice H Eagly, Inge Brechan, Matthew J Lindberg, and Lisa Merrill. 2009. Feeling validated versus being correct: a meta-analysis of selective exposure to information. Psychological bulletin, Vol. 135, 4 (2009), 555.

[46]

Del Harvey. 2019. Helping you find reliable public health information on Twitter. https://blog.twitter.com/en_us/topics/company/2019/helping-you-find-reliable-public-health-information-on-twitter.html. (Accessed on 09/11/2020).

[47]

Del Harvey and David Gasca. 2018. Serving healthy conversation. https://blog.twitter.com/official/en_us/topics/product/2018/Serving_Healthy_Conversation.html. (Accessed on 09/11/2020).

[48]

MS Heen, Joel D Lieberman, and Terance D Miethe. 2014. A comparison of different online sampling approaches for generating national samples. Center for Crime and Justice Policy, Vol. 1, 9 (2014), 1--8.

[49]

John Hegeman. 2018. Facing Facts: Facebook's Fight Against Misinformation - About Facebook. https://about.fb.com/news/2018/05/facing-facts-facebooks-fight-against-misinformation/. (Accessed on 09/11/2020).

[50]

Jane Im, Sonali Tandon, Eshwar Chandrasekharan, Taylor Denby, and Eric Gilbert. 2020. Synthesized social signals: Computationally-derived social signals from account histories. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1--12.

Digital Library

[51]

Twitter Inc. 2019. The Twitter Rules. https://help.twitter.com/en/rules-and-policies/twitter-rules. (Accessed on 09/13/2019).

[52]

Peter John, Graham Smith, and Gerry Stoker. 2009. Nudge nudge, think think: two strategies for changing civic behaviour. The Political Quarterly, Vol. 80, 3 (2009), 361--370.

[53]

Hollyn M Johnson and Colleen M Seifert. 1994. Sources of the continued influence effect: When misinformation in memory affects later inferences. J. Exp. Psychol. Learn. Mem. Cogn., Vol. 20, 6 (1994), 1420.

[54]

Shipi Kankane, Carlina DiRusso, and Christen Buckley. 2018. Can we nudge users toward better password management?: An initial study. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, LBW593.

Digital Library

[55]

Johannes Kiesel, Maria Mestre, Rishabh Shukla, Emmanuel Vincent, Payam Adineh, David Corney, Benno Stein, and Martin Potthast. 2019. Semeval-2019 task 4: Hyperpartisan news detection. In Proceedings of the 13th International Workshop on Semantic Evaluation. 829--839.

[56]

Silvia Knobloch-Westerwick and Jingbo Meng. 2009. Looking the other way: Selective exposure to attitude-consistent and counterattitudinal political information. Communication Research, Vol. 36, 3 (2009), 426--448.

[57]

Silvia Knobloch-Westerwick, Nikhil Sharma, Derek L Hansen, and Scott Alter. 2005. Impact of popularity indications on readers' selective exposure to online news. J. Broadcast. Electron. Media, Vol. 49, 3 (2005), 296--313.

[58]

D. Koehler and N. Harvey. 2004. In D. Koehler & N. Harvey (Eds.). (2004). Blackwell handbook of judgment and decision making (pp. 62--88). Oxford, UK: Blackwell. (2004), 62--88.

[59]

Andrew Kohut, Carroll Doherty, Michael Dimock, and Scott Keeter. 2012. Cable leads the pack as campaign news source. Pew Center for the People and the Press. Retrieved from https://www.pewresearch.org/wp-content/uploads/sites/4/legacy-pdf/2012-Communicating-Release.pdf (2012).

[60]

Geza Kovacs, Zhengxuan Wu, and Michael S Bernstein. 2021. Not Now, Ask Later: Users Weaken Their Behavior Change Regimen Over Time, But Expect To Re-Strengthen It Imminently. arXiv preprint arXiv:2101.11743 (2021).

[61]

Issie Lapowski. 2018. NewsGuard Wants to Fight Fake News with Humans, Not Algorithms.

[62]

Kenton Lee, Luheng He, Mike Lewis, and Luke Zettlemoyer. 2017. End-to-end neural coreference resolution. arXiv preprint arXiv:1707.07045 (2017).

[63]

Min Kyung Lee, Sara Kiesler, and Jodi Forlizzi. 2011. Mining behavioral economics to design persuasive technology for healthy choices. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 325--334.

Digital Library

[64]

Birthe A Lehmann, Gretchen B Chapman, Frits ME Franssen, Gerjo Kok, and Robert AC Ruiter. 2016. Changing the default to promote influenza vaccination among health care workers. Vaccine, Vol. 34, 11 (2016), 1389--1392.

[65]

Jordan Litman, Tiffany Hutchins, and Ryan Russon. 2005. Epistemic curiosity, feeling-of-knowing, and exploratory behaviour. Cognition & Emotion, Vol. 19, 4 (2005), 559--582.

[66]

Elizabeth Lopatto. 2020. In its latest confusing decision, Twitter reinstates The New York Post - The Verge. https://www.theverge.com/2020/10/30/21542801/twitter-lifts-ny-post-ban-policy-changes. (Accessed on 04/05/2021).

[67]

Tessa Lyons. 2017. Replacing Disputed Flags With Related Articles - About Facebook. https://about.fb.com/news/2017/12/news-feed-fyi-updates-in-our-fight-against-misinformation/. (Accessed on 09/11/2020).

[68]

Tessa Lyons. 2018. Hard Questions: How Is Facebook's Fact-Checking Program Working? - About Facebook. https://about.fb.com/news/2018/06/hard-questions-fact-checking/. (Accessed on 09/11/2020).

[69]

Diane M Mackie and Sarah Queller. 2000. The impact of group membership on persuasion: Revisiting “Who says what to whom with what effect?”. Attitudes, behavior, and social context: The role of norms and group membership (2000), 135--155.

[70]

Rakoen Maertens, Jon Roozenbeek, Melisa Basol, and Sander van der Linden. 2020. Long-term effectiveness of inoculation against misinformation: Three longitudinal experiments. Journal of Experimental Psychology: Applied (2020).

[71]

Zlatina Marinova, Jochen Spangenberg, Denis Teyssou, Symeon Papadopoulos, Nikos Sarris, Alexandre Alaphilippe, and Kalina Bontcheva. 2020. Weverify: Wider and Enhanced Verification for You Project Overview and Tools. In 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 1--4.

[72]

Mediabiasfactcheck. 2019. About - Media Bias/Fact Check. https://mediabiasfactcheck.com/about/. (Accessed on 09/18/2019).

[73]

Solomon Messing and Sean J Westwood. 2014. Selective exposure in the age of social media: Endorsements trump partisan source affiliation when selecting news online. Communication research, Vol. 41, 8 (2014), 1042--1063.

[74]

Miriam J Metzger. 2007. Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research. Journal of the American Society for Information Science and Technology, Vol. 58, 13 (2007), 2078--2091.

Digital Library

[75]

Miriam J Metzger, Andrew J Flanagin, and Ryan B Medders. 2010. Social and heuristic approaches to credibility evaluation online. Journal of communication, Vol. 60, 3 (2010), 413--439.

[76]

Miriam J Metzger, Ethan H Hartsell, and Andrew J Flanagin. 2015. Cognitive dissonance or credibility? A comparison of two theoretical explanations for selective exposure to partisan news. Communication Research (2015), 0093650215613136.

[77]

Philip Meyer. 1988. Defining and measuring credibility of newspapers: Developing an index. Journalism quarterly, Vol. 65, 3 (1988), 567--574.

[78]

Amy Mitchell, Jeffrey Gottfried, Jocelyn Kiley, and Katerina Eva Matsa. 2014. Political polarization & media habits. http://www.journalism.org/2014/10/21/political-polarization-media-habits/. Pew Research Center, Vol. 21 (2014).

[79]

Tanushree Mitra, Clayton J Hutto, and Eric Gilbert. 2015. Comparing person-and process-centric strategies for obtaining quality data on amazon mechanical turk. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. 1345--1354.

Digital Library

[80]

Tanushree Mitra, Graham P Wright, and Eric Gilbert. 2017. A parsimonious language model of social media credibility across disparate events. In Proc. CSCW. ACM, 126--145.

Digital Library

[81]

Adam Mosseri. 2016. Addressing Hoaxes and Fake News - About Facebook. https://about.fb.com/news/2016/12/news-feed-fyi-addressing-hoaxes-and-fake-news/. (Accessed on 09/11/2020).

[82]

Elmie Nekmat. 2020. Nudge Effect of Fact-Check Alerts: Source Influence and Media Skepticism on Sharing of News Misinformation in Social Media. Social Media+Society, Vol. 6, 1 (2020), 2056305119897322.

[83]

Onora O'neill. 2002. A question of trust: The BBC Reith Lectures 2002 .Cambridge University Press.

[84]

OpenSources. 2018. OpenSources. http://opensources.co.

[85]

Souneil Park, Seungwoo Kang, Sangyoung Chung, and Junehwa Song. 2009. NewsCube: delivering multiple aspects of news to mitigate media bias. In Proceedings of the SIGCHI conference on human factors in computing systems. 443--452.

Digital Library

[86]

Jessica Paynter, Sarah Luskin-Saxby, Deb Keen, Kathryn Fordyce, Grace Frost, Christine Imms, Scott Miller, David Trembath, Madonna Tucker, and Ullrich Ecker. 2019. Evaluation of a template for countering misinformation-Real-world Autism treatment myth debunking. PloS one, Vol. 14, 1 (2019).

[87]

Cornelia Pechmann. 1992. Predicting when two-sided ads will be more effective than one-sided ads: The role of correlational and correspondent inferences. Journal of Marketing Research, Vol. 29, 4 (1992), 441--453.

[88]

Gordon Pennycook, Adam Bear, Evan T Collins, and David G Rand. 2020 a. The implied truth effect: Attaching warnings to a subset of fake news headlines increases perceived accuracy of headlines without warnings. Management Science (2020).

[89]

Gordon Pennycook, Ziv Epstein, Mohsen Mosleh, Antonio A Arechar, Dean Eckles, and David Rand. 2019. Understanding and reducing the spread of misinformation online. Unpublished manuscript: https://psyarxiv. com/3n9u8 (2019).

[90]

Gordon Pennycook, Jonathon McPhetres, Yunhao Zhang, Jackson G Lu, and David G Rand. 2020 b. Fighting COVID-19 misinformation on social media: Experimental evidence for a scalable accuracy-nudge intervention. Psychological science, Vol. 31, 7 (2020), 770--780.

[91]

Gordon Pennycook and David G Rand. 2017. Assessing the effect of "disputed" warnings and source salience on perceptions of fake news accuracy. (2017).

[92]

Gordon Pennycook and David G Rand. 2019. Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences, Vol. 116, 7 (2019), 2521--2526.

[93]

Richard E Petty and John T Cacioppo. 1986. The elaboration likelihood model of persuasion. In Communication and persuasion. Springer, 1--24.

[94]

Charlie Pinder, Jo Vermeulen, Russell Beale, and Robert Hendley. 2015. Subliminal priming of nonconscious goals on smartphones. In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. 825--830.

Digital Library

[95]

Sara Pluviano, Caroline Watt, and Sergio Della Sala. 2017. Misinformation lingers in memory: failure of three pro-vaccination strategies. PLoS One, Vol. 12, 7 (2017), e0181640.

[96]

THE MEDIA INSIGHT PROJECT. 2018. Americans and the News Media: What they do - and don't - understand about each other - American Press Institute. https://www.americanpressinstitute.org/publications/reports/survey-research/americans-and-the-news-media/. (Accessed on 09/07/2020).

[97]

Vahed Qazvinian, Emily Rosengren, Dragomir R Radev, and Qiaozhu Mei. 2011. Rumor has it: Identifying misinformation in microblogs. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 1589--1599.

Digital Library

[98]

Muck Rack. 2019. Muck Rack | For Journalists. https://muckrack.com/journalists. (Accessed on 09/14/2019).

[99]

Marilyn Roberts, Wayne Wanta, and Tzong-Horng Dzwo. 2002. Agenda setting and issue salience online. Communication research, Vol. 29, 4 (2002), 452--465.

[100]

Jon Roozenbeek and Sander van der Linden. 2019. Fake news game confers psychological resistance against online misinformation. Palgrave Communications, Vol. 5, 1 (2019), 1--10.

[101]

Guy Rosen. 2020. An Update on Our Work to Keep People Informed and Limit Misinformation About COVID-19 - About Facebook. https://about.fb.com/news/2020/04/covid-19-misinfo-update/. (Accessed on 09/11/2020).

[102]

Guy Rosen and Tessa Lyons. 2019. Remove, Reduce, Inform: New Steps to Manage Problematic Content - About Facebook. https://about.fb.com/news/2019/04/remove-reduce-inform-new-steps/. (Accessed on 09/11/2020).

[103]

Yoel Roth and Ashita Achuthan. 2020. Building rules in public: Our approach to synthetic & manipulated media. https://blog.twitter.com/en_us/topics/company/2020/new-approach-to-synthetic-and-manipulated-media.html. (Accessed on 09/11/2020).

[104]

Yoel Roth and Nick Pickles. 2020. Updating our approach to misleading information. https://blog.twitter.com/en_us/topics/product/2020/updating-our-approach-to-misleading-information.html. (Accessed on 09/11/2020).

[105]

Twitter Safety. 2019. Strengthening our approach to deliberate attempts to mislead voters. https://blog.twitter.com/en_us/topics/company/2019/strengthening-our-approach-to-deliberate-attempts-to-mislead-vot.html. (Accessed on 09/11/2020).

[106]

Twitter Safety. 2020. Expanding our policies to further protect the civic conversation. https://blog.twitter.com/en_us/topics/company/2020/civic-integrity-policy-update.html. (Accessed on 09/11/2020).

[107]

Emily Saltz, Tommy Shane, Victoria Kwan, Claire Leibowicz, and Claire Wardle. 2020. It matters how platforms label manipulated media. Here are 12 principles designers should follow. - The Partnership on AI. https://www.partnershiponai.org/it-matters-how-platforms-label-manipulated-media-here-are-12-principles-designers-should-follow/. (Accessed on 07/01/2020).

[108]

Evan Selinger and Kyle Whyte. 2011. Is there a right way to nudge? The practice and ethics of choice architecture. Sociology Compass, Vol. 5, 10 (2011), 923--935.

[109]

Alina Selyukh, Maria Hollenhorst, and Katie Park. 2016. Disney-Fox Deal: Who Controls Digital Media? Conglomerates, Brands In One Chart|NPR. https://www.npr.org/sections/alltechconsidered/2016/10/28/ 499495517/big-media-companies-and-their-many-brands-in-one-chart.

[110]

Chengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Kai-Cheng Yang, Alessandro Flammini, and Filippo Menczer. 2018. The spread of low-credibility content by social bots. Nature communications, Vol. 9, 1 (2018), 1--9.

[111]

Henry Silverman. 2019. Helping Fact-Checkers Identify False Claims Faster - About Facebook. https://about.fb.com/news/2019/12/helping-fact-checkers/. (Accessed on 09/11/2020).

[112]

Jeff Smith. 2019. Designing Against Misinformation - Facebook Design - Medium. https://medium.com/facebook-design/designing-against-misinformation-e5846b3aa1e2. (Accessed on 09/18/2019).

[113]

Jeff Smith, Alex Leavitt, and Grace Jackson. 2018. Designing New Ways to Give Context to News Stories | Facebook Newsroom. https://newsroom.fb.com/news/2018/04/inside-feed-article-context/.

[114]

Anselm Strauss and Juliet Corbin. 1994. Grounded theory methodology. Handbook of qualitative research, Vol. 17 (1994), 273--85.

[115]

Jay Sullivan. 2020. Introducing a Forwarding Limit on Messenger - About Facebook. https://about.fb.com/news/2020/09/introducing-a-forwarding-limit-on-messenger/. (Accessed on 09/11/2020).

[116]

Róbert Sumi, Taha Yasseri, et al. 2011. Edit wars in Wikipedia. In 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing. IEEE, 724--727.

[117]

S Shyam Sundar. 2008. The MAIN model: A heuristic approach to understanding technology effects on credibility. Digital media, youth, and credibility, Vol. 73100 (2008).

[118]

S Shyam Sundar, Haiyan Jia, T Franklin Waddell, and Yan Huang. 2015. Toward a theory of interactive media effects (TIME). The handbook of the psychology of communication technology (2015), 47--86.

[119]

S Shyam Sundar, Anne Oeldorf-Hirsch, and Qian Xu. 2008. The bandwagon effect of collaborative filtering technology. In CHI'08 extended abstracts. ACM, 3453--3458.

Digital Library

[120]

Cass R Sunstein. 2014. Why nudge?: The politics of libertarian paternalism .Yale University Press.

[121]

Cass R Sunstein. 2015. The ethics of nudging. Yale J. on Reg., Vol. 32 (2015), 413.

[122]

Cass R Sunstein. 2016. Do people like nudges? (2016).

[123]

Cass R Sunstein. 2017. Nudges that fail. Behavioural Public Policy, Vol. 1, 1 (2017), 4--25.

[124]

Twitter Support. 2020. New labels for government and state-affiliated media accounts. https://blog.twitter.com/en_us/topics/product/2020/new-labels-for-government-and-state-affiliated-media-accounts.html. (Accessed on 09/11/2020).

[125]

David Tannenbaum, Craig R Fox, and Todd Rogers. 2017. On the misplaced politics of behavioural policy interventions. Nature Human Behaviour, Vol. 1, 7 (2017), 0130.

[126]

Richard H Thaler. 2008. Nudge: Improving decisions about health, wealth, and happiness.

[127]

Sreethu Thulasi. 2019. Understand Why You're Seeing Certain Ads and How You Can Adjust Your Ad Experience - About Facebook. https://about.fb.com/news/2019/07/understand-why-youre-seeing-ads/. (Accessed on 09/11/2020).

[128]

Peter M. Todd and Gerd Gigerenzer. 2000. Pré cis of Simple heuristics that make us smart. Behavioral and Brain Sciences, Vol. 23, 5 (2000), 727--780. https://doi.org/10.1017/S0140525X00003447

[129]

Yariv Tsfati. 2010. Online news exposure and trust in the mainstream media: Exploring possible associations. American Behavioral Scientist, Vol. 54, 1 (2010), 22--42.

[130]

Yariv Tsfati and Joseph N Cappella. 2003. Do people watch what they do not trust? Exploring the association between news media skepticism and exposure. Communication Research, Vol. 30, 5 (2003), 504--529.

[131]

Yariv Tsfati and Joseph N Cappella. 2005. Why do people watch news they do not trust? The need for cognition as a moderator in the association between news media skepticism and exposure. Media psychology, Vol. 7, 3 (2005), 251--271.

[132]

Twitter. 2019. Notices on Twitter and what they mean. https://help.twitter.com/en/rules-and-policies/notices-on-twitter. (Accessed on 09/11/2020).

[133]

Yang Wang, Pedro Giovanni Leon, Alessandro Acquisti, Lorrie Faith Cranor, Alain Forget, and Norman Sadeh. 2014. A field trial of privacy nudges for facebook. In Proc. CHI. ACM, 2367--2376.

Digital Library

[134]

Yang Wang, Pedro Giovanni Leon, Kevin Scott, Xiaoxuan Chen, Alessandro Acquisti, and Lorrie Faith Cranor. 2013. Privacy nudges for social media: an exploratory Facebook study. In Proceedings of the 22nd International Conference on World Wide Web. 763--770.

Digital Library

[135]

Claire Wardle. 2019. Misinformation Has Created a New World Disorder - Scientific American. https://www.scientificamerican.com/article/misinformation-has-created-a-new-world-disorder/. (Accessed on 05/27/2020).

[136]

Thomas Wood and Ethan Porter. 2019. The elusive backfire effect: Mass attitudes' steadfast factual adherence. Political Behavior, Vol. 41, 1 (2019), 135--163.

[137]

Robin Worrall. 2020. Social media used to spread, create COVID-19 falsehoods -- Harvard Gazette. https://news.harvard.edu/gazette/story/2020/05/social-media-used-to-spread-create-covid-19-falsehoods/. (Accessed on 09/12/2020).

[138]

Caiming Xiong, Victor Zhong, and Richard Socher. 2016. Dynamic coattention networks for question answering. arXiv preprint arXiv:1611.01604 (2016).

[139]

Amy X Zhang, Aditya Ranganathan, Sarah Emlen Metz, Scott Appling, Connie Moon Sehat, Norman Gilmore, Nick B Adams, Emmanuel Vincent, Jennifer Lee, Martin Robbins, et al. 2018. A structured response to misinformation: Defining and annotating credibility indicators in news articles. In Companion Proceedings of the The Web Conference 2018. 603--612.

Digital Library

[140]

Zhe Zhao, Paul Resnick, and Qiaozhu Mei. 2015. Enquiring minds: Early detection of rumors in social media from enquiry posts. In Proceedings of the 24th international conference on world wide web. 1395--1405.

Digital Library

Cited By

Dehghan SPir Mohammadiani RMohammadi S(2025)The credibility assessment of Twitter/X users based organization objectives by heterogeneous resources in big data life cycleComputers in Human Behavior10.1016/j.chb.2024.108428162:COnline publication date: 7-Jan-2025
https://dl.acm.org/doi/10.1016/j.chb.2024.108428
Medina L(2024)“Fridays Are Racist”International Journal of Technoethics10.4018/IJT.34402515:1(1-19)Online publication date: 17-May-2024
https://doi.org/10.4018/IJT.344025
Pak JKim H(2024)The Role of Content Labeling and Discrete Emotions in User Participation in a COVID-19 U.S. Reddit CommunityJournalism & Mass Communication Quarterly10.1177/10776990241257588Online publication date: 24-Jul-2024
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Index Terms

NudgeCred: Supporting News Credibility Assessment on Social Media Through Nudges
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
    2. HCI design and evaluation methods
      1. User studies

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 5, Issue CSCW2

CSCW2

October 2021

5376 pages

EISSN:2573-0142

DOI:10.1145/3493286

Editor:
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Apple Inc., United States

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Published: 18 October 2021

Published in PACMHCI Volume 5, Issue CSCW2

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Dehghan SPir Mohammadiani RMohammadi S(2025)The credibility assessment of Twitter/X users based organization objectives by heterogeneous resources in big data life cycleComputers in Human Behavior10.1016/j.chb.2024.108428162:COnline publication date: 7-Jan-2025
https://dl.acm.org/doi/10.1016/j.chb.2024.108428
Medina L(2024)“Fridays Are Racist”International Journal of Technoethics10.4018/IJT.34402515:1(1-19)Online publication date: 17-May-2024
https://doi.org/10.4018/IJT.344025
Pak JKim H(2024)The Role of Content Labeling and Discrete Emotions in User Participation in a COVID-19 U.S. Reddit CommunityJournalism & Mass Communication Quarterly10.1177/10776990241257588Online publication date: 24-Jul-2024
https://doi.org/10.1177/10776990241257588
Hartwig KDoell FReuter C(2024)The Landscape of User-centered Misinformation Interventions - A Systematic Literature ReviewACM Computing Surveys10.1145/367472456:11(1-36)Online publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1145/3674724
Tang HLenzini GGreiff SRohles BSergeeva A(2024)“Who Knows? Maybe it Really Works”: Analysing Users' Perceptions of Health Misinformation on Social MediaProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661510(1499-1517)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661510
Malki LPatel DSingh A(2024)"The Headline Was So Wild That I Had To Check": An Exploration of Women's Encounters With Health Misinformation on Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/36374058:CSCW1(1-26)Online publication date: 26-Apr-2024
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Pyle CZhang BHaimson OAndalibi N(2024)"I'm Constantly in This Dilemma": How Migrant Technology Professionals Perceive Social Media Recommendation AlgorithmsProceedings of the ACM on Human-Computer Interaction10.1145/36373428:CSCW1(1-33)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637342
Yaqub WKay JGoldwater M(2024)Foundations for Enabling People to Recognise Misinformation in Social Media News based on Retracted ScienceProceedings of the ACM on Human-Computer Interaction10.1145/36373358:CSCW1(1-38)Online publication date: 26-Apr-2024
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Zhang YSun JFeng LYao CFan MZhang LWang QGeng XRui Y(2024)See Widely, Think Wisely: Toward Designing a Generative Multi-agent System to Burst Filter BubblesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642545(1-24)Online publication date: 11-May-2024
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Hughes EWang RJuneja PLi TMitra TZhang A(2024)Viblio: Introducing Credibility Signals and Citations to Video-Sharing PlatformsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642490(1-20)Online publication date: 11-May-2024
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