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The Future of False Information Detection on Social Media: New Perspectives and Trends

Authors:

Zhiwen YuAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 53, Issue 4

Article No.: 68, Pages 1 - 36

https://doi.org/10.1145/3393880

Published: 11 July 2020 Publication History

Abstract

The massive spread of false information on social media has become a global risk, implicitly influencing public opinion and threatening social/political development. False information detection (FID) has thus become a surging research topic in recent years. As a promising and rapidly developing research field, we find that much effort has been paid to new research problems and approaches of FID. Therefore, it is necessary to give a comprehensive review of the new research trends of FID. We first give a brief review of the literature history of FID, based on which we present several new research challenges and techniques of it, including early detection, detection by multimodal data fusion, and explanatory detection. We further investigate the extraction and usage of various crowd intelligence in FID, which paves a promising way to tackle FID challenges. Finally, we give our views on the open issues and future research directions of FID, such as model adaptivity/generality to new events, embracing of novel machine learning models, aggregation of crowd wisdom, adversarial attack and defense in detection models, and so on.

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Pereira BHa S(2024)ENVIRONMENTAL ISSUES ON TIKTOK: TOPICS AND CLAIMS OF MISLEADING INFORMATIONJournal of Baltic Science Education10.33225/jbse/24.23.13123:1(131-150)Online publication date: 29-Feb-2024
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Caled DCarvalho PSousa FSilva M(2024)DOMAIN: Explainable Credibility Assessment Tools for Empowering Online Readers Coping with MisinformationACM Transactions on the Web10.1145/369647219:1(1-31)Online publication date: 26-Oct-2024
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Index Terms

The Future of False Information Detection on Social Media: New Perspectives and Trends
1. Human-centered computing
  1. Collaborative and social computing
2. Information systems
  1. World Wide Web
    1. Web applications
      1. Social networks

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 53, Issue 4

July 2021

831 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3410467

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Published: 11 July 2020

Online AM: 07 May 2020

Accepted: 01 April 2020

Revised: 01 March 2020

Received: 01 August 2019

Published in CSUR Volume 53, Issue 4

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Pereira BHa S(2024)ENVIRONMENTAL ISSUES ON TIKTOK: TOPICS AND CLAIMS OF MISLEADING INFORMATIONJournal of Baltic Science Education10.33225/jbse/24.23.13123:1(131-150)Online publication date: 29-Feb-2024
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https://dl.acm.org/doi/10.1145/3696472
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