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Social bots significantly influence public discourse and opinion, but their capabilities are limited. Hybrid human-bot systems offer promising interactions but challenge current propaganda detection methods.

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Area of Science:

  • Computer Science
  • Political Science
  • Sociology

Background:

  • Social bots are influential in public discourse and opinion formation.
  • Their role in propaganda distribution and election influence is suspected.
  • The definition of social bots lacks consensus across disciplines.

Purpose of the Study:

  • To define social bots and explore their operational mechanisms and limitations.
  • To investigate human-bot integration for enhanced capabilities.
  • To address challenges in detecting hybrid propaganda.

Main Methods:

  • Literature review and analysis of social bot functionalities.
  • Examination of Twitter as a case study for bot operations.
  • Discussion of human-in-the-loop approaches for bot control.

Main Results:

  • Social bots have technical limitations despite advances in AI and Big Data.
  • Integrating humans with bots (hybridization) shows potential for meaningful interactions.
  • Hybrid systems pose detection challenges for political propaganda.

Conclusions:

  • A balanced definition of social bots is proposed.
  • Human-bot hybridization is the most promising avenue for advanced interactions.
  • Sophisticated detection mechanisms are needed to counter hybrid propaganda.