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Recognition of Antisocial Behavior in Online Discussions

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Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019 (ISAT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1051))

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Abstract

The paper is focused on recognition of antisocial behavior in social media. User generated content in the form of discussions is essential to the success of many online platforms. While most users tend to civil accepting the social norms, others engage in antisocial behavior negatively affecting the rest of the community and its goals. Such behavior includes harassment, bullying, flaming, trolling, etc. The contribution is focused on classification of troll posts in online discussions to distinguish them from creditable posts. The work proposes a machine learning approach to build the classification model for toxic posts identification on an extensive dataset. The following machine learning methods were used: k Nearest Neighbors, Naïve Bayes Classifier, Decision Trees, Logistic regression and Support Vector Machine. These machine learning methods were used in combination with three different feature representations of texts of online discussions as a binary vector, a bag of words and the TF-IDF weighting scheme. The paper contains also the results of experiments with all learned models for toxic posts recognition.

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Acknowledgements

The work presented in this paper was supported by the Slovak Research and Development Agency under the contract No. APVV-017-0267 “Automated Recognition of Antisocial Behavior in Online Communities” and the contract No. APVV-015-0731.

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Authors and Affiliations

  1. Technical University, Letná 9, 04200, Košice, Slovakia

    Kristína Machová & Dominik Kolesár

Authors
  1. Kristína Machová
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  2. Dominik Kolesár
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Corresponding author

Correspondence to Kristína Machová .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Jerzy Świątek

  2. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Leszek Borzemski

  3. University of Applied Sciences in Nysa, Nysa, Poland

    Zofia Wilimowska

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Machová, K., Kolesár, D. (2020). Recognition of Antisocial Behavior in Online Discussions. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019. ISAT 2019. Advances in Intelligent Systems and Computing, vol 1051. Springer, Cham. https://doi.org/10.1007/978-3-030-30604-5_23

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