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Identifying Right-Wing Extremism in German Twitter Profiles: A Classification Approach

  • Matthias Hartung
  • Roman Klinger
  • Franziska Schmidtke
  • Lars Vogel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10260)

Abstract

Social media platforms are used by an increasing number of extremist political actors for mobilization, recruiting or radicalization purposes. We propose a machine learning approach to support manual monitoring aiming at identifying right-wing extremist content in German Twitter profiles. We frame the task as profile classification, based on textual cues, traits of emotionality in language use, and linguistic patterns. A quantitative evaluation reveals a limited precision of 25% with a close-to-perfect recall of 95%. This leads to a considerable reduction of the workload of human analysts in detecting right-wing extremist users.

Keywords

Extremism monitoring Classification Social media 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Matthias Hartung
    • 1
    • 2
  • Roman Klinger
    • 2
    • 3
  • Franziska Schmidtke
    • 4
  • Lars Vogel
    • 4
  1. 1.Semantic Computing Group, CITECBielefeld UniversityBielefeldGermany
  2. 2.Semalytix GmbHBielefeldGermany
  3. 3.Institut für Maschinelle SprachverarbeitungUniversity of StuttgartStuttgartGermany
  4. 4.Kompetenzzentrum RechtsextremismusFriedrich-Schiller-Universität JenaJenaGermany

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