Social Debunking of Misinformation on WhatsApp: The Case for Strong and In-group Ties

Author:

Pasquetto Irene V.1,Jahani Eaman2,Atreja Shubham3,Baum Matthew4

Affiliation:

1. University of Michigan & Harvard Kennedy School, Ann Arbor, MI, USA

2. MIT, Cambridge, MA, USA

3. University of Michigan, Ann Arbor, MI, USA

4. Harvard University, Cambridge, MA, USA

Abstract

In this paper, we argue that WhatsApp can play an important role in correcting misinformation. We show how specific WhatsApp affordances (flexibility in format and audience selection) and existing social capital (prevalence of strong ties; homophily in political groups) can be leveraged to maximize the re-sharing of debunking messages, such as those accessed by WhatsApp users via ChatBots and Tip-Lines. Debunking messages received in the format of audio files generated more interest and were more effective in correcting beliefs than text- or image-based messages. In addition, we found clear evidence that users re-share debunks at higher rates when they received them from people close to them (strong ties), from individuals who generally agree with them politically (in-group members), or when both conditions are met. We suggest that WhatsApp leverages our findings to maximize the re-share of those fact-checks that are already circulating on the platform by using the existing social capital in the network, unlocking the potential for such debunks to reach a larger audience on WhatsApp.

Funder

Omidyar Network

Bill and Melinda Gates Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Reference100 articles.

1. 2020. Social Media and Democracy: The State of the Field , Prospects for Reform . Cambridge University Press . Https://doi.org/10.1017/9781108890960 10.1017/9781108890960 2020. Social Media and Democracy: The State of the Field, Prospects for Reform. Cambridge University Press. Https://doi.org/10.1017/9781108890960

2. Amelia Acker . 2018 . Data Craft: The Manipulation of Social media metadata . Data and Society . https://datasociety.net/wp-content/uploads/2018/11/DS_Data_Craft_Manipulation_of_Social_Media_Metadata.pdf Amelia Acker. 2018. Data Craft: The Manipulation of Social media metadata. Data and Society. https://datasociety.net/wp-content/uploads/2018/11/DS_Data_Craft_Manipulation_of_Social_Media_Metadata.pdf

3. Syeda Zainab Akbar Divyanshu Kukreti Somya Sagarika and Joyojeet Pal. 2020. Temporal patterns in Covid 19 misinformation in India. http://joyojeet.people.si.umich.edu/temporal-patterns-in-covid-19-misinformation-in-india/. Syeda Zainab Akbar Divyanshu Kukreti Somya Sagarika and Joyojeet Pal. 2020. Temporal patterns in Covid 19 misinformation in India. http://joyojeet.people.si.umich.edu/temporal-patterns-in-covid-19-misinformation-in-india/.

4. Tackling misinformation: What researchers could do with social media data;Amazeen Michelle A;The Harvard Kennedy School Misinformation Review,2020

5. Michelle A Amazeen , Emily Thorson , Ashley Muddiman , and Lucas Graves . 2015. A comparison of correction formats: The effectiveness and effects of rating scale versus contextual corrections on misinformation . American Press Institute . Downloaded April 27 ( 2015 ), 2015. Michelle A Amazeen, Emily Thorson, Ashley Muddiman, and Lucas Graves. 2015. A comparison of correction formats: The effectiveness and effects of rating scale versus contextual corrections on misinformation. American Press Institute. Downloaded April 27 (2015), 2015.

Cited by 22 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3