Disinformation in the Online Information Ecosystem: Detection, Mitigation and Challenges
Amrita Bhattacharjee, Kai Shu, Min Gao, Huan Liu

TL;DR
This paper surveys the challenges and approaches in detecting and mitigating online disinformation, especially during the COVID-19 infodemic, highlighting computational and interdisciplinary strategies.
Contribution
It provides a comprehensive overview of recent disinformation detection and mitigation techniques, emphasizing the complexities introduced by the COVID-19 pandemic.
Findings
Disinformation detection is complex due to the noisy online environment.
Mitigation strategies involve computational and interdisciplinary methods.
The COVID-19 infodemic has intensified disinformation challenges.
Abstract
With the rapid increase in access to internet and the subsequent growth in the population of online social media users, the quality of information posted, disseminated and consumed via these platforms is an issue of growing concern. A large fraction of the common public turn to social media platforms and in general the internet for news and even information regarding highly concerning issues such as COVID-19 symptoms. Given that the online information ecosystem is extremely noisy, fraught with misinformation and disinformation, and often contaminated by malicious agents spreading propaganda, identifying genuine and good quality information from disinformation is a challenging task for humans. In this regard, there is a significant amount of ongoing research in the directions of disinformation detection and mitigation. In this survey, we discuss the online disinformation problem,…
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Taxonomy
TopicsMisinformation and Its Impacts · Spam and Phishing Detection · Advanced Malware Detection Techniques
