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A Survey of Datasets for Information Diffusion Tasks

6 July 2024
Fuxia Guo
Xiaowen Wang
Yanwei Xie
Z. J. Wang
Jingqiu Li
Lanjun Wang
ArXiv (abs)PDFHTML
Main:9 Pages
2 Figures
Bibliography:5 Pages
13 Tables
Appendix:1 Pages
Abstract

Information diffusion across various new media platforms gradually influences perceptions, decisions, and social behaviors of individual users. In communication studies, the famous Five W's of Communication model (5W Model) has displayed the process of information diffusion clearly. At present, although plenty of studies and corresponding datasets about information diffusion have emerged, a systematic categorization of tasks and an integration of datasets are still lacking. To address this gap, we survey a systematic taxonomy of information diffusion tasks and datasets based on the "5W Model" framework. We first categorize the information diffusion tasks into ten subtasks with definitions and datasets analysis, from three main tasks of information diffusion prediction, social bot detection, and misinformation detection. We also collect the publicly available dataset repository of information diffusion tasks with the available links and compare them based on six attributes affiliated to users and content: user information, social network, bot label, propagation content, propagation network, and veracity label. In addition, we discuss the limitations and future directions of current datasets and research topics to advance the future development of information diffusion. The dataset repository can be accessed at our website this https URL.

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@article{guo2025_2407.05161,
  title={ A Survey of Datasets for Information Diffusion Tasks },
  author={ Fuxia Guo and Xiaowen Wang and Yanwei Xie and Zehao Wang and Jingqiu Li and Lanjun Wang },
  journal={arXiv preprint arXiv:2407.05161},
  year={ 2025 }
}
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