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Identifying Artificial Actors in E-Dating: A Probabilistic Segmentation Based on Interactional Pattern Analysis

  • Andreas Schmitz
  • Olga Yanenko
  • Marcel Hebing
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

We propose different behaviour and interaction related indicators of artificial actors (bots) and show how they can be separated from natural users in a virtual dating market. A finite mixture classification model is applied on the different behavioural and interactional information to classify users into bot vs. non-bot-categories. Finally the validity of the classification model and the impact of bots on sociodemographic distributions and scientific analysis is discussed.

Keywords

Artificial Actor Finite Mixture Model Latent Variable Approach Artificial User Fake Profile 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Chair of Sociology IUniversity of BambergBambergGermany
  2. 2.Chair for Computing in the Cultural SciencesUniversity of BambergBambergGermany
  3. 3.Socio-Economic Panel Study (SOEP), DIW BerlinBerlinGermany

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