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

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Challenges at the Interface of Data Analysis, Computer Science, and Optimization

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.

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Notes

  1. 1.

    http://en.wikipedia.org/

  2. 2.

    http://eu.battle.net/wow/

  3. 3.

    http://messenger.yahoo.com/

  4. 4.

    Due to privacy reasons the visual message check was done by the online-dating provider.

  5. 5.

    A chi-square test on predicted vs. actual bots yielded a Cramer’s V of 0. 7156 (χ2 = 1, 000, p = 0. 00).

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Author information

Authors and Affiliations

  1. Chair of Sociology I, University of Bamberg, Wilhelmsplatz 3, 96045, Bamberg, Germany

    Andreas Schmitz

  2. Chair for Computing in the Cultural Sciences, University of Bamberg, Feldkirchenstrasse 21, 96045, Bamberg, Germany

    Olga Yanenko

  3. Socio-Economic Panel Study (SOEP), DIW Berlin, Mohrenstrasse 58, 10117, Berlin, Germany

    Marcel Hebing

Authors
  1. Andreas Schmitz
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  2. Olga Yanenko
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  3. Marcel Hebing
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Corresponding author

Correspondence to Olga Yanenko .

Editor information

Editors and Affiliations

  1. Fak. Wirtschaftswissenschaften, Inst. Entscheidungstheorieund, Universität Karlsruhe (TH), Kaiserstr. 12, Karlsruhe, 76128, Germany

    Wolfgang A. Gaul

  2. Insitute for Information Systems, and Management (IISM), Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, 76131, Baden-Württemberg, Germany

    Andreas Geyer-Schulz

  3. , Information Systems, University ofHildesheim, Marienburger Platz 22, Hildesheim, 31141, Germany

    Lars Schmidt-Thieme

  4. Institute for Information Systems, and Management (IISM), Karlsruhe Institute of Technology (KIT), Kaiserstraße 12, Karlsruhe, 76128, Germany

    Jonas Kunze

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Schmitz, A., Yanenko, O., Hebing, M. (2012). Identifying Artificial Actors in E-Dating: A Probabilistic Segmentation Based on Interactional Pattern Analysis. In: Gaul, W., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds) Challenges at the Interface of Data Analysis, Computer Science, and Optimization. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24466-7_33

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