Authors

Herun Wan, Minnan Luo, Zihan Ma, Guang Dai, and Xiang Zhao

Resources

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Introduction

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, named MisBot. 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.

Citation

If our work helps you, please cite us:

@inproceedings{wan-etal-2025-social,
    title = "How Do Social Bots Participate in Misinformation Spread? A Comprehensive Dataset and Analysis",
    author = "Wan, Herun  and
      Luo, Minnan  and
      Ma, Zihan  and
      Dai, Guang  and
      Zhao, Xiang",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.emnlp-main.1604/",
    pages = "31481--31504",
    ISBN = "979-8-89176-332-6"
}
Contact

If you have any questions, you could submit an issue on GitHub or contact Herun Wan using wanherun at stu.xjtu.edu.cn.