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Detecting bots with temporal logic.

Social bots are computer programs that act like human users on social media platforms. Social bot detection is a rapidly growing field dominated by machine learning approaches. In this paper, we propose a complementary method to machine learning by exploring bot detection as a model checking problem...

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Published in:Synthese Vol. 202; no. 3; pp. 1 - 40
Main Authors: Pedersen, Mina Young, Slavkovik, Marija, Smets, Sonja
Format: Article
Published: Springer Nature Sep2023
Online Access:View this record in EBSCOhost
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      pub: Springer Nature
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        10.1007/s11229-023-04264-6
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          Pedersen, Mina Young
          Slavkovik, Marija
          Smets, Sonja
        affil:
          Department of Information Science and Media Studies, University of Bergen, 5007, Bergen, Norway
          ILLC, University of Amsterdam, 1098 XG, Amsterdam, The Netherlands
      sug:
      keyword:
        Bot detection
        Hybrid logic
        Model checking
        Social bots
        Social network logic
        Temporal logic
      ab: Social bots are computer programs that act like human users on social media platforms. Social bot detection is a rapidly growing field dominated by machine learning approaches. In this paper, we propose a complementary method to machine learning by exploring bot detection as a model checking problem. We introduce Temporal Network Logic (TNL) which we use to specify social networks where agents can post and follow each other. Using this logic, we formalize different types of social bot behavior with formulas that are satisfied in a model of a network with bots. We also consider an extension of the logic where we explore the expressive power of including elements from hybrid logic in our framework. We give model checking algorithms for TNL and its hybrid extension, and show that the complexity of the former is in p and the latter in pspace.
      pubtype: Academic Journal
      doctype: Article
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    language: English
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      custom: Synthese is a copyright of Springer, 2023. All Rights Reserved.
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