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Mitigating the Spread of Misinformation Through Design

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Computer-Human Interaction Research and Applications (CHIRA 2021, CHIRA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1882))

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Abstract

This paper presents a novel approach to mitigating the spread of misinformation by presenting social media design principles based on users’ interaction tendencies. The focus of our design principles is to provide new design affordances to make the truth louder. This research leverages users’ high and low interaction tendencies to amplify truth by increasing users’ interactions with verified posts and decreasing their interactions with unverified posts. The paper describes a theoretical basis and 3 design principles, and presents an analysis of participants’ responses to the design principles. In addition, this paper investigates users’ views on sharing and preference for platform-based incentives. The results show that users with lower interaction tendencies share verified information more when they receive additional interaction support. Furthermore, due to the interaction tendencies, users exhibit opposite preferences for platform-based incentives that can encourage their participation in making the truth louder. Users with high interaction tendencies prefer incentives that highlight their presence on the platform, and users with low interaction tendencies favor incentives that can educate them about the impact of their participation on their friends and community.

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References

  1. Acquisti, A., et al.: Nudges for privacy and security: understanding and assisting users’ choices online. ACM Comput. Surv. (CSUR) 50(3), 1–41 (2017)

    Article  Google Scholar 

  2. Arif, A., Shanahan, K., Chou, F.J., Dosouto, Y., Starbird, K., Spiro, E.S.: How information snowballs: Exploring the role of exposure in online rumor propagation. In: Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, pp. 466–477. ACM (2016)

    Google Scholar 

  3. Babu, A., Liu, A., Zhang, J.: New updates to reduce clickbait headlines, May 2017. https://about.fb.com/news/2017/05/news-feed-fyi-new-updates-to-reduce-clickbait-headlines/

  4. Bentley, F., Quehl, K., Wirfs-Brock, J., Bica, M.: Understanding online news behaviors. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–11 (2019)

    Google Scholar 

  5. Bhuiyan, M.M., Zhang, K., Vick, K., Horning, M.A., Mitra, T.: 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, pp. 205–208 (2018)

    Google Scholar 

  6. Chen, A., Lu, Y., Chau, P.Y., Gupta, S.: Classifying, measuring, and predicting users’ overall active behavior on social networking sites. J. Manag. Inf. Syst. 31(3), 213–253 (2014)

    Article  Google Scholar 

  7. Coleman, K.: Introducing birdwatch, a community-based approach to misinformation, January 2021. https://blog.twitter.com/en_us/topics/product/2021/introducing-birdwatch-a-community-based-approach-to-misinformation.html

  8. Crowell, C.: Our approach to bots and misinformation (2017). https://blog.twitter.com/en_us/topics/company/2017/Our-Approach-Bots-Misinformation.html

  9. Flintham, M., Karner, C., Bachour, K., Creswick, H., Gupta, N., Moran, S.: Falling for fake news: investigating the consumption of news via social media. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–10 (2018)

    Google Scholar 

  10. Fogg, B.J.: A behavior model for persuasive design. In: Proceedings of the 4th international Conference on Persuasive Technology, pp. 1–7 (2009)

    Google Scholar 

  11. Geeng, C., Yee, S., Roesner, F.: 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, pp. 1–14 (2020)

    Google Scholar 

  12. Gerson, J., Plagnol, A.C., Corr, P.J.: Passive and active facebook use measure (paum): validation and relationship to the reinforcement sensitivity theory. Personality Individ. Differ. 117, 81–90 (2017)

    Article  Google Scholar 

  13. Gleicher, N.: Removing coordinated inauthentic behavior from china, August 2019. https://about.fb.com/news/2019/08/removing-cib-china/

  14. Grace, L., Hone, B.: Factitious: Large scale computer game to fight fake news and improve news literacy. In: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–8 (2019)

    Google Scholar 

  15. Hughes, T., Smith, J., Leavitt, A.: Helping people better assess the stories they see in news feed with the context button, April 2018. https://about.fb.com/news/2018/04/news-feed-fyi-more-context/

  16. Khan, M.L.: Social media engagement: what motivates user participation and consumption on youtube? Comput. Hum. Behav. 66(4), 236–247 (2017)

    Article  Google Scholar 

  17. Kumar, S., Shah, N.: False information on web and social media: A survey. arXiv preprint arXiv:1804.08559 (2018)

  18. Lewandowsky, S., Ecker, U.K., Cook, J.: Beyond misinformation: Understanding and coping with the “post-truth” era. J. Appl. Res. Memory Cogn. 6(4), 353–369 (2017)

    Google Scholar 

  19. Lewandowsky, S., Ecker, U.K., Seifert, C.M., Schwarz, N., Cook, J.: Misinformation and its correction: continued influence and successful debiasing. Psychol. Sci. Public Interest 13(3), 106–131 (2012)

    Article  Google Scholar 

  20. Likas, A., Vlassis, N., Verbeek, J.J.: The global k-means clustering algorithm. Pattern Recogn. 36(2), 451–461 (2003)

    Article  Google Scholar 

  21. Marwick, A.E.: Why do people share fake news? a sociotechnical model of media effects. Georgetown Law Technol. Rev. 2(2), 474–512 (2018)

    Google Scholar 

  22. Mele, N., et al.: Combating fake news: An agenda for research and action. Retrieved on October 17, 2018 (2017)

    Google Scholar 

  23. Morris, M.R., Counts, S., Roseway, A., Hoff, A., Schwarz, J.: Tweeting is believing? understanding microblog credibility perceptions. In: Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work, pp. 441–450 (2012)

    Google Scholar 

  24. Nekmat, E.: Nudge effect of fact-check alerts: Source influence and media skepticism on sharing of news misinformation in social media. Social Media+ Society 6(1), 2056305119897322 (2020)

    Google Scholar 

  25. Nonnecke, B., Preece, J.: Shedding light on lurkers in online communities. Ethnographic Studies in Real and Virtual Environments: Inhabited Information Spaces and Connected Communities, Edinburgh 123128 (1999)

    Google Scholar 

  26. Pennycook, G., McPhetres, J., Zhang, Y., Lu, J.G., Rand, D.G.: Fighting covid-19 misinformation on social media: experimental evidence for a scalable accuracy-nudge intervention. Psychol. Sci. 31(7), 770–780 (2020)

    Article  Google Scholar 

  27. Perez, E.B., King, J., Watanabe, Y.H., Chen, X.: Counterweight: Diversifying news consumption. In: Adjunct Publication of the 33rd Annual ACM Symposium on User Interface Software and Technology. pp. 132–134 (2020)

    Google Scholar 

  28. politifact: New test with related articles (2021). https://www.politifact.com/

  29. Preece, J., Shneiderman, B.: The reader-to-leader framework: motivating technology-mediated social participation. AIS Trans. Human-comput. Interact. 1(1), 13–32 (2009)

    Article  Google Scholar 

  30. Roozenbeek, J., van der Linden, S.: Fake news game confers psychological resistance against online misinformation. Palgrave Commun. 5(1), 1–10 (2019)

    Article  Google Scholar 

  31. Rosen, G.: How we’re tackling misinformation across our apps (2021). https://about.fb.com/news/2021/03/how-were-tackling-misinformation-across-our-apps/

  32. Rosen, G., Lyons, T.: Remove, reduce, inform: New steps to manage problematic content (2019). https://about.fb.com/news/2019/04/remove-reduce-inform-new-steps/

  33. Roth, Y., Harvey, D.: How twitter is fighting spam and malicious automation (2018). https://blog.twitter.com/en_us/topics/company/2018/how-twitter-is-fighting-spam-and-malicious-automation.html

  34. Roth, Y., Pickles, N.: Updating our approach to misleading information (2020). https://blog.twitter.com/en_us/topics/product/2020/updating-our-approach-to-misleading-information.html

  35. Shao, G.: Understanding the appeal of user-generated media: a uses and gratification perspective. Internet Res. 19(1), 7–25 (2009)

    Article  Google Scholar 

  36. Siddiqui, S., Maher, M.L.: Reframing the fake news problem: Social media interaction design to make the truth louder. In: CHIRA, pp. 158–165 (2021)

    Google Scholar 

  37. Siddiqui, S., Maher, M.L.: Active-passive framework for developing communication strategies to combat misinformation. In: Proceedings of the 19th International Conference on Web Based Communities and Social Media (2022)

    Google Scholar 

  38. Smith, J.: Designing against misinformation (2017). https://medium.com/facebook-design/designing-against-misinformation-e5846b3aa1e2

  39. Starbird, K.: Examining the alternative media ecosystem through the production of alternative narratives of mass shooting events on twitter. In: Eleventh International AAAI Conference on Web and Social Media (2017)

    Google Scholar 

  40. Starbird, K., Arif, A., Wilson, T., Van Koevering, K., Yefimova, K., Scarnecchia, D.: Ecosystem or echo-system? exploring content sharing across alternative media domains. In: Proceedings of the International AAAI Conference on Web and Social Media. vol. 12 (2018)

    Google Scholar 

  41. Su, S.: New test with related articles (2017). https://about.fb.com/news/2017/04/news-feed-fyi-new-test-with-related-articles/

  42. Thaler, R.H., Sunstein, C.R.: Nudge: Improving decisions about health, wealth, and happiness. Penguin (2009)

    Google Scholar 

  43. Torres, R., Gerhart, N., Negahban, A.: Combating fake news: An investigation of information verification behaviors on social networking sites. In: Proceedings of the 51st Hawaii International Conference on System Sciences (2018)

    Google Scholar 

  44. Trifiro, B.M., Gerson, J.: Social media usage patterns: Research note regarding the lack of universal validated measures for active and passive use. Social Media+ Society 5(2), 2056305119848743 (2019)

    Google Scholar 

  45. Yaqub, W., Kakhidze, O., Brockman, M.L., Memon, N., Patil, S.: Effects of credibility indicators on social media news sharing intent. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–14 (2020)

    Google Scholar 

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Authors and Affiliations

  1. University of North Carolina, Charlotte, NC, USA

    Safat Siddiqui & Mary Lou Maher

Authors
  1. Safat Siddiqui
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  2. Mary Lou Maher
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Correspondence to Safat Siddiqui .

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Editors and Affiliations

  1. Medical University Graz, Graz, Austria

    Andreas Holzinger

  2. IT- Institute of Telecommunications, Lisbon, Portugal

    Hugo Plácido da Silva

  3. Université Catholique de Louvain, Louvain-la-Neuve, Belgium

    Jean Vanderdonckt

  4. Madeira Interactive Technologies Institute, Funchal, Portugal

    Larry Constantine

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Siddiqui, S., Maher, M.L. (2023). Mitigating the Spread of Misinformation Through Design. In: Holzinger, A., da Silva, H.P., Vanderdonckt, J., Constantine, L. (eds) Computer-Human Interaction Research and Applications. CHIRA CHIRA 2021 2022. Communications in Computer and Information Science, vol 1882. Springer, Cham. https://doi.org/10.1007/978-3-031-41962-1_2

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  • DOI: https://doi.org/10.1007/978-3-031-41962-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-41961-4

  • Online ISBN: 978-3-031-41962-1

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