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Discriminating bot accounts based solely on temporal features of microblog behavior

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  • Pan, Junshan
  • Liu, Ying
  • Liu, Xiang
  • Hu, Hanping

Abstract

As the largest microblog service in China, Sina Weibo has attracted numerous automated applications (known as bots) due to its popularity and open architecture. We classify the active users from Sina Weibo into human, bot-based and hybrid groups based solely on the study of temporal features of their posting behavior. The anomalous burstiness parameter and time-interval entropy value are exploited to characterize automation. We also reveal different behavior patterns among the three types of users regarding their reposting ratio, daily rhythm and active days. Our findings may help Sina Weibo manage a better community and should be considered for dynamic models of microblog behaviors.

Suggested Citation

  • Pan, Junshan & Liu, Ying & Liu, Xiang & Hu, Hanping, 2016. "Discriminating bot accounts based solely on temporal features of microblog behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 193-204.
    • Handle: RePEc:eee:phsmap:v:450:y:2016:i:c:p:193-204
    DOI: 10.1016/j.physa.2015.12.148
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    References listed on IDEAS

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    1. Pan, Junshan & Hu, Hanping & Liu, Ying, 2014. "Human behavior during Flash Crowd in web surfing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 212-219.
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    Cited by:

    1. Qi Li & Cong Wei & Jianning Dang & Lei Cao & Li Liu, 2020. "Tracking and Analyzing Public Emotion Evolutions During COVID-19: A Case Study from the Event-Driven Perspective on Microblogs," IJERPH, MDPI, vol. 17(18), pages 1-24, September.

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