How Do Social Bots Participate in Misinformation Spread? A Comprehensive Dataset and Analysis
August 18, 2024 Β· Declared Dead Β· π Conference on Empirical Methods in Natural Language Processing
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Authors
Herun Wan, Minnan Luo, Zihan Ma, Guang Dai, Xiang Zhao
arXiv ID
2408.09613
Category
cs.SI: Social & Info Networks
Cross-listed
cs.CY
Citations
6
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
5 months ago
Abstract
Social media platforms provide an ideal environment to spread misinformation, where social bots can accelerate the spread. This paper explores the interplay between social bots and misinformation on the Sina Weibo platform. We construct a large-scale dataset that includes annotations for both misinformation and social bots. From the misinformation perspective, the dataset is multimodal, containing 11,393 pieces of misinformation and 16,416 pieces of verified information. From the social bot perspective, this dataset contains 65,749 social bots and 345,886 genuine accounts, annotated using a weakly supervised annotator. Extensive experiments demonstrate the comprehensiveness of the dataset, the clear distinction between misinformation and real information, and the high quality of social bot annotations. Further analysis illustrates that: (i) social bots are deeply involved in information spread; (ii) misinformation with the same topics has similar content, providing the basis of echo chambers, and social bots would amplify this phenomenon; and (iii) social bots generate similar content aiming to manipulate public opinions.
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