A Survey on the Role of Crowds in Combating Online Misinformation: Annotators, Evaluators, and Creators

A curated list of papers on "A Survey on the Role of Crowds in Combating Online Misinformation: Annotators, Evaluators, and Creators" (Paper link)

Citation

 @article{he2023survey,
  title={A Survey on the Role of Crowds in Combating Online Misinformation: Annotators, Evaluators, and Creators},
  author={He, Bing and Hu, Yibo and Lee, Yeon-Chang and Oh, Soyoung and Verma, Gaurav and Kumar, Srijan},
  journal={arXiv preprint arXiv:2310.02095},
  year={2023}
}

Online misinformation poses a global risk with significant real-world consequences. To combat misinformation, current research relies on professionals like journalists and fact-checkers for annotating and debunking false information, while also developing automated machine learning methods for detecting misinformation. Complementary to these approaches, recent research has increasingly concentrated on utilizing the power of ordinary social media users, a.k.a. “the crowd”, who act as eyes-on-the-ground proactively questioning and countering misinformation. Notably, recent studies show that 96% of counter-misinformation responses originate from them. Acknowledging their prominent role, we present the first systematic and comprehensive survey of research papers that actively leverage the crowds to combat misinformation.

In this survey, we first identify 88 papers related to crowd-based efforts, following a meticulous annotation process adhering to the PRISMA framework (preferred reporting items for systematic reviews and meta-analyses). We then present key statistics related to misinformation, counter-misinformation, and crowd input in different formats and topics. Upon holistic analysis of the papers, we introduce a novel taxonomy of the roles played by the crowds in combating misinformation: (i) crowds as annotators who actively identify misinformation; (ii) crowds as evaluators who assess counter-misinformation effectiveness; (iii) crowds as creators who create counter-misinformation.

This taxonomy explores the crowd’s capabilities in misinformation detection, identifies the prerequisites for effective counter-misinformation, and analyzes crowd-generated counter-misinformation. In each assigned role, we conduct a detailed analysis to categorize the specific utilization of the crowd. Particularly, we delve into (i) distinguishing individual, collaborative, and machine-assisted labeling for annotators; (ii) analyzing the effectiveness of counter-misinformation through surveys, interviews, and in-lab experiments for evaluators; and (iii) characterizing creation patterns and creator profiles for creators. Finally, we conclude this survey by outlining potential avenues for future research in this field.

References

2022

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Birds of a feather don't fact-check each other: Partisanship and the evaluation of news in Twitter's Birdwatch crowdsourced fact-checking program Annotator 2022 Conference on Human Factors in Computing Systems - Proceedings Association for Computing Machinery https://www.doi.org/10.1145/3491102.3502040
Crowd Sourcing and Blockchain-Based Incentive Mechanism to Combat Fake News Annotator 2022 Studies in Computational Intelligence Springer Science and Business Media Deutschland GmbH https://www.doi.org/10.1007/978-3-030-90087-8_15
Social Debunking of Misinformation on WhatsApp: The Case for Strong and In-group Ties Evaluator 2022 Proceedings of the ACM on Human-Computer Interaction Association for Computing Machinery https://www.doi.org/10.1145/3512964
Election Fraud and Misinformation on Twitter: Author, Cluster, and Message Antecedents Evaluator 2022 Media and Communication Cogitatio Press https://www.doi.org/10.17645/mac.v10i2.5168
Debunking health myths on the internet: the persuasive effect of (visual) online communication Evaluator 2022 Journal of Public Health (Germany) Springer Science and Business Media Deutschland GmbH https://www.doi.org/10.1007/s10389-022-01694-3
A comparison of prebunking and debunking interventions for implied versus explicit misinformation Evaluator 2022 British Journal of Psychology nan https://pubmed.ncbi.nlm.nih.gov/34967004/
The effects of self-generated and other-generated eWOM in inoculating against misinformation Evaluator 2022 Telematics and Informatics Elsevier Ltd https://www.doi.org/10.1016/j.tele.2022.101835
Does Wording Matter? Examining the Effect of Phrasing on Memory for Negated Political Fact Checks Evaluator 2022 Journal of Applied Research in Memory and Cognition Society for Applied Research in Memory and Cognition https://www.doi.org/10.1037/mac0000022
Effects of corrections on COVID-19-related misinformation: cross-media empirical analyses in Japan Evaluator 2022 International Journal of Web Based Communities Inderscience Publishers https://www.doi.org/10.1504/IJWBC.2022.122389
Factors influencing fake news rebuttal acceptance during the COVID-19 pandemic and the moderating effect of cognitive ability Evaluator 2022 Computers in Human Behavior Elsevier Ltd https://www.doi.org/10.1016/j.chb.2021.107174
The Influence of Media Trust and Normative Role Expectations on the Credibility of Fact Checkers Evaluator 2022 Journalism Practice Routledge https://www.doi.org/10.1080/17512786.2022.2080102
What If Unmotivated Is More Dangerous? The Motivation-Contingent Effectiveness of Misinformation Correction on Social Media Evaluator 2022 International Journal of Communication University of Southern California https://ijoc.org/index.php/ijoc/article/view/17510
Correcting science misinformation in an authoritarian country: An experiment from China Evaluator 2022 Telematics and Informatics Elsevier Ltd https://www.doi.org/10.1016/j.tele.2021.101749
Science Factionalism: How Group Identity Language Affects Public Engagement With Misinformation and Debunking Narratives on a Popular Q&A Platform in China Creator 2022 Social Media and Society SAGE Publications Ltd https://www.doi.org/10.1177/20563051221077019
Exploring the Effect of Spreading Fake News Debunking Based on Social Relationship Networks Creator 2022 Frontiers in Physics Frontiers Media S.A. https://www.doi.org/10.3389/fphy.2022.833385
The impact of psycholinguistic patterns in discriminating between fake news spreaders and fact checkers Creator 2022 Data and Knowledge Engineering Elsevier B.V. https://www.doi.org/10.1016/j.datak.2021.101960
Reading between the lies: A classification scheme of types of reply to misinformation in public discussion threads Creator 2022 CHIIR 2022 - Proceedings of the 2022 Conference on Human Information Interaction and Retrieval Association for Computing Machinery, Inc https://www.doi.org/10.1145/3498366.3505823
Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic Creator 2022 Information Processing and Management Elsevier Ltd https://www.doi.org/10.1016/j.ipm.2022.102935
The use of emotions in conspiracy and debunking videos to engage publics on YouTube Creator 2022 New Media and Society SAGE Publications Ltd https://www.doi.org/10.1177/14614448221105877
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2021

Title Category Year Venue Publisher URL
HawkEye: A robust reputation system for community-based counter-misinformation Annotator 2021 Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2021 Association for Computing Machinery, Inc https://www.doi.org/10.1145/3487351.3488343
Can the crowd judge truthfulness? A longitudinal study on recent misinformation about COVID-19 Annotator 2021 Personal and Ubiquitous Computing Springer Science and Business Media Deutschland GmbH https://www.doi.org/10.1007/s00779-021-01604-6
The many dimensions of truthfulness: Crowdsourcing misinformation assessments on a multidimensional scale Annotator 2021 Information Processing and Management Elsevier Ltd https://www.doi.org/10.1016/j.ipm.2021.102710
‘It infuriates me': examining young adults’ reactions to and recommendations to fight misinformation about COVID-19 Evaluator 2021 Journal of Youth Studies Routledge https://www.doi.org/10.1080/13676261.2021.1965108
The Effects of a News Literacy Video and Real-Time Corrections to Video Misinformation Related to Sunscreen and Skin Cancer Evaluator 2021 Health Communication Routledge https://www.doi.org/10.1080/10410236.2021.1910165
Scaling up fact-checking using the wisdom of crowds Evaluator 2021 Science Advances American Association for the Advancement of Science https://www.doi.org/10.1126/sciadv.abf4393
You’re definitely wrong, maybe: Correction style has minimal effect on corrections of misinformation online Evaluator 2021 Media and Communication Cogitatio Press https://www.doi.org/10.17645/mac.v9i1.3519
The Role of Influence of Presumed Influence and Anticipated Guilt in Evoking Social Correction of COVID-19 Misinformation Evaluator 2021 Health Communication Routledge https://www.doi.org/10.1080/10410236.2021.1888452
Evaluating Rumor Debunking Effectiveness During the COVID-19 Pandemic Crisis: Utilizing User Stance in Comments on Sina Weibo Evaluator 2021 Frontiers in Public Health Frontiers Media S.A. https://www.doi.org/10.3389/fpubh.2021.770111
Why do citizens share covid‐19 fact‐checks posted by chinese government social media accounts? The elaboration likelihood model Evaluator 2021 International Journal of Environmental Research and Public Health MDPI https://www.doi.org/10.3390/ijerph181910058
Prevalence of anger, engaged in sadness: engagement in misinformation, correction, and emotional tweets during mass shootings Creator 2021 Online Information Review Emerald Group Holdings Ltd. https://www.doi.org/10.1108/OIR-03-2021-0121
Young Adults' Ability To Detect Fake News And Their New Media Literacy Level In The Wake Of The Covid-19 Pandemic Creator 2021 Journal of Content, Community and Communication nan https://www.amity.edu/gwalior/jccc/pdf/jun_31.pdf
Arresting fake news sharing on social media: a theory of planned behavior approach Creator 2021 Management Research Review Emerald Group Holdings Ltd. https://www.doi.org/10.1108/MRR-05-2020-0286
"There is No Corona; It’s a Conspiracy": Addressing the Perceptions of People about COVID-19 through the Narrative of Their Comments on Social Media Creator 2021 Journal of Consumer Health on the Internet Routledge https://www.doi.org/10.1080/15398285.2020.1867412
Raising the flag: Monitoring user perceived disinformation on reddit Creator 2021 Information (Switzerland) MDPI AG https://www.doi.org/10.3390/info12010004
SAMS: Human-in-the-loop approach to combat the sharing of digital misinformation Creator 2021 CEUR Workshop Proceedings CEUR-WS https://arodes.hes-so.ch/record/8922
Fighting disaster misinformation in Latin America: the #19S Mexican earthquake case study Creator 2021 Personal and Ubiquitous Computing Springer Science and Business Media Deutschland GmbH https://www.doi.org/10.1007/s00779-020-01411-5
Dynamics of social corrections to peers sharing COVID-19 misinformation on WhatsApp in Brazil Creator 2021 Journal of the American Medical Informatics Association : JAMIA NLM (Medline) https://www.doi.org/10.1093/jamia/ocab219

2020

Title Category Year Venue Publisher URL
Investigating Differences in Crowdsourced News Credibility Assessment: Raters, Tasks, and Expert Criteria Annotator 2020 Proceedings of the ACM on Human-Computer Interaction Association for Computing Machinery https://www.doi.org/10.1145/3415164
WhistleBlower: Towards A Decentralized and Open Platform for Spotting Fake News Annotator 2020 Proceedings - 2020 IEEE International Conference on Blockchain, Blockchain 2020 Institute of Electrical and Electronics Engineers Inc. https://www.doi.org/10.1109/Blockchain50366.2020.00026
A reliable weighting scheme for the aggregation of crowd intelligence to detect fake news Annotator 2020 Information (Switzerland) MDPI AG https://www.doi.org/10.3390/INFO11060319
“Is It the Message or the Messenger?”: Conspiracy Endorsement and Media Sources Evaluator 2020 Social Science Computer Review SAGE Publications Inc. https://www.doi.org/10.1177/0894439320965107
Seeking Formula for Misinformation Treatment in Public Health Crises: The Effects of Corrective Information Type and Source Evaluator 2020 Health Communication Routledge https://www.doi.org/10.1080/10410236.2019.1573295
Exploring “Angry” and “Like” Reactions on Uncivil Facebook Comments That Correct Misinformation in the News Evaluator 2020 Digital Journalism Routledge https://www.doi.org/10.1080/21670811.2020.1835512
An Eye Tracking Approach to Understanding Misinformation and Correction Strategies on Social Media: The Mediating Role of Attention and Credibility to Reduce HPV Vaccine Misperceptions Evaluator 2020 Health Communication Routledge https://www.doi.org/10.1080/10410236.2020.1787933
Feeling angry: the effects of vaccine misinformation and refutational messages on negative emotions and vaccination attitude Evaluator 2020 Journal of Health Communication Bellwether Publishing, Ltd. https://www.doi.org/10.1080/10810730.2020.1838671
Countering Fake News: A Comparison of Possible Solutions Regarding User Acceptance and Effectiveness Evaluator 2020 Proceedings of the ACM on Human-Computer Interaction Association for Computing Machinery https://www.doi.org/10.1145/3415211
Caution: Rumors ahead—A case study on the debunking of false information on Twitter Evaluator 2020 Big Data and Society SAGE Publications Ltd https://www.doi.org/10.1177/2053951720980127
The Battle is On: Factors that Motivate People to Combat Anti-Vaccine Misinformation Creator 2020 Health Communication Routledge https://www.doi.org/10.1080/10410236.2020.1838108
Information literacy competence in curtailing fake news about the COVID-19 pandemic among undergraduates in Nigeria Creator 2020 Reference Services Review Emerald Group Holdings Ltd. https://www.doi.org/10.1108/RSR-06-2020-0037
To correct or not to correct? Social identity threats increase willingness to denounce fake news through presumed media influence and hostile media perceptions Creator 2020 Communication Research Reports Routledge https://www.doi.org/10.1080/08824096.2020.1841622
The Role of the Crowd in Countering Misinformation: A Case Study of the COVID-19 Infodemic Creator 2020 Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020 Institute of Electrical and Electronics Engineers Inc. https://www.doi.org/10.1109/BigData50022.2020.9377956
COVID-19 and the 5G conspiracy theory: Social network analysis of twitter data Creator 2020 Journal of Medical Internet Research JMIR Publications Inc. https://www.doi.org/10.2196/19458
Misinformation debunking and cross-platform information sharing through Twitter during Hurricanes Harvey and Irma: a case study on shelters and ID checks Creator 2020 Natural Hazards Springer https://www.doi.org/10.1007/s11069-020-04016-6
Characterizing COVID-19 misinformation communities using a novel twitter dataset Creator 2020 CEUR Workshop Proceedings CEUR-WS https://arxiv.org/abs/2008.00791
Refuting fake news on social media: nonprofits, crisis response strategies and issue involvement Creator 2020 Journal of Product and Brand Management Emerald Group Holdings Ltd. https://www.doi.org/10.1108/JPBM-12-2018-2146
Social media rumor refuter feature analysis and crowd identification based on XG Boost and NLP Creator 2020 Applied Sciences (Switzerland) MDPI AG https://www.doi.org/10.3390/app10144711
#Arson Emergency and Australia’s “Black Summer”: Polarisation and Misinformation on Social Media Creator 2020 Disinformation in Open Online Media Springer https://link.springer.com/chapter/10.1007/978-3-030-61841-4_11

2019

Title Category Year Venue Publisher URL
Exposure to Countering Messages Online: Alleviating or Strengthening False Belief? Evaluator 2019 Cyberpsychology, Behavior, and Social Networking Mary Ann Liebert Inc. https://www.doi.org/10.1089/cyber.2019.0227
Fighting misinformation on social media using crowdsourced judgments of news source quality Evaluator 2019 Proceedings of the National Academy of Sciences of the United States of America National Academy of Sciences https://www.doi.org/10.1073/pnas.1806781116
Temporal trends in anti-vaccine discourse on Twitter Creator 2019 Vaccine Elsevier Ltd https://www.doi.org/10.1016/j.vaccine.2019.06.086
Learning from fact-checkers: Analysis and generation of fact-checking language Creator 2019 SIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval Association for Computing Machinery, Inc https://www.doi.org/10.1145/3331184.3331248
Is citizen journalism better than professional journalism for fact-checking rumours in China? How Weibo users verified information following the 2015 Tianjin blasts Creator 2019 Global Media and China SAGE Publications Ltd https://www.doi.org/10.1177/2059436419834124
Diffusion of pro- and anti-false information tweets: the Black Panther movie case Creator 2019 Computational and Mathematical Organization Theory Springer New York LLC https://www.doi.org/10.1007/s10588-018-09286-x
Different faces of false: The spread and curtailment of false information in the black Panther Twitter discussion Creator 2019 Journal of Data and Information Quality Association for Computing Machinery https://www.doi.org/10.1145/3339468
Debunking rumors on social media: The use of denials Creator 2019 Computers in Human Behavior Elsevier Ltd https://www.doi.org/10.1016/j.chb.2019.02.022

2018

Title Category Year Venue Publisher URL
Hybrid machine-crowd approach for fake news detection Annotator 2018 Proceedings - 4th IEEE International Conference on Collaboration and Internet Computing, CIC 2018 Institute of Electrical and Electronics Engineers Inc. https://www.doi.org/10.1109/CIC.2018.00048
See Something, Say Something: Correction of Global Health Misinformation on Social Media Evaluator 2018 Health Communication Routledge https://www.doi.org/10.1080/10410236.2017.1331312
Salient beliefs about sharing rumor denials on the Internet Creator 2018 ACM International Conference Proceeding Series Association for Computing Machinery https://www.doi.org/10.1145/3164541.3164578
Rumor response, debunking response, and decision makings of misinformed Twitter users during disasters Creator 2018 Natural Hazards Springer Netherlands https://www.doi.org/10.1007/s11069-018-3344-6

2017

Title Category Year Venue Publisher URL
An analysis of rumor and counter-rumor messages in social media Annotator 2017 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Springer Verlag https://www.doi.org/10.1007/978-3-319-70232-2_22
The Retransmission of Rumor and Rumor Correction Messages on Twitter Creator 2017 American Behavioral Scientist SAGE Publications Inc. https://www.doi.org/10.1177/0002764217717561
A study of tweet veracity to separate rumours from counter-rumours Creator 2017 ACM International Conference Proceeding Series Association for Computing Machinery https://www.doi.org/10.1145/3097286.3097290
A closer look at the self-correcting crowd: Examining corrections in online rumors Creator 2017 Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW Association for Computing Machinery https://www.doi.org/10.1145/2998181.2998294
Does KFC sell rat? Analysis of tweets in the wake of a rumor outbreak Creator 2017 Aslib Journal of Information Management Emerald Group Publishing Ltd. https://www.doi.org/10.1108/AJIM-01-2017-0026

2016

Title Category Year Venue Publisher URL
Changing conspiracy beliefs through rationality and ridiculing Evaluator 2016 Frontiers in Psychology Frontiers Research Foundation https://www.doi.org/10.3389/fpsyg.2016.01525
Analysing how people orient to and spread rumours in social media by looking at conversational threads Creator 2016 PLoS ONE Public Library of Science https://www.doi.org/10.1371/journal.pone.0150989
An exploration of rumor combating behavior on social media in the context of social crises Creator 2016 Computers in Human Behavior Elsevier Ltd https://www.doi.org/10.1016/j.chb.2015.11.054
Toward understanding how users respond to rumours in social media Creator 2016 Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 Institute of Electrical and Electronics Engineers Inc. https://www.doi.org/10.1109/ASONAM.2016.7752326

2015

Title Category Year Venue Publisher URL
CREDBANK: A large-scale social media corpus with associated credibility annotations Annotator 2015 Proceedings of the 9th International Conference on Web and Social Media, ICWSM 2015 AAAI Press https://ojs.aaai.org/index.php/ICWSM/article/view/14625
Reducing conspiracy theory beliefs Evaluator 2015 Psihologija Serbian Psychological Society https://www.doi.org/10.2298/PSI1503251S
Crowdsourced rumour identification during emergencies Evaluator 2015 WWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web Association for Computing Machinery, Inc https://www.doi.org/10.1145/2740908.2742573

2013

Title Category Year Venue Publisher URL
Analysis of microblog rumors and correction texts for disaster situations Creator 2013 ACM International Conference Proceeding Series nan https://www.doi.org/10.1145/2539150.2539184