How Do Social Bots Participate in Misinformation Spread? A Comprehensive Dataset and Analysis

August 18, 2024 Β· Declared Dead Β· πŸ› 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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