Skip to main content
SpringerLink
Log in

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

  • Conference paper
  • First Online:
Natural Language Processing and Information Systems (NLDB 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.facebook.com, https://www.youtube.com.

  2. 2.

    All English Tweets are translated to German via Google translate (http://translate.google.com) to receive a more comprehensive training set.

  3. 3.

    https://dev.twitter.com/rest/public.

References

  1. Amadeu-Antonio-Stiftung: Rechtsextreme und menschenverachtende Phänomene im Social Web (2016). https://www.amadeu-antonio-stiftung.de/w/files/pdfs/monitoringbericht-2015.pdf

  2. Ashcroft, M., Fisher, A., Kaati, L., Omer, E., Prucha, N.: Detecting jihadist messages on twitter. In: Proceedings of EISIC (2015)

    Google Scholar 

  3. Berger, J.: Nazis vs. ISIS on Twitter. A Comparative Study of White Nationalist and ISIS Online Social Media Networks. Tech. rep., Center for Cyber and Homeland Security, George Washington University, Washington, D.C. (2016)

    Google Scholar 

  4. Blanquart, G., Cook, D.: Twitter influence and cumulative perceptions of extremist support. a case study of geert wilders. In: Proceedings of ACTC (2013)

    Google Scholar 

  5. Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20, 273–297 (1995)

    MATH  Google Scholar 

  6. Ferrara, E., Wang, W.Q., Varol, O., Flammini, A., Galstyan, A.: Predicting online extremism, content adopters, and interaction reciprocity (2016). arxiv: https://arxiv.org/abs/1605.00659

  7. Kaati, L., Omer, E., Prucha, N., Shrestha, A.: Detecting multipliers of jihadism on twitter. In: IEEE International Conference on Data Mining Workshop (ICDMW) (2015)

    Google Scholar 

  8. Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)

    Book  MATH  Google Scholar 

  9. Parmelee, J., Bichars, S.: Politics and the Twitter Revolution. Lexington Books, Landham, MD (2013)

    Google Scholar 

  10. Plutchik, R.: The nature of emotions. American Scientist (2001)

    Google Scholar 

  11. Quent, M., Salheiser, A., Schmidtke, F.: Gefährdungen der demokratischen Kultur in Thüringen (2016). http://www.denkbunt-thueringen.de/wp-content/uploads/2016/02/Gef%C3%A4hrdungsanalyse.pdf

  12. Scanlon, J.R., Gerber, M.S.: Automatic detection of cyber-recruitment by violent extremists. Secur. Inform. 3(1), 5 (2014)

    Article  Google Scholar 

  13. Stöss, R.: Rechtsextremismus im Wandel. Friedrich-Ebert-Stiftung, Berlin (2010)

    Google Scholar 

  14. Suttles, J., Ide, N.: Distant supervision for emotion classification with discrete binary values. In: Gelbukh, A. (ed.) CICLing 2013. LNCS, vol. 7817, pp. 121–136. Springer, Heidelberg (2013). doi:10.1007/978-3-642-37256-8_11

    Chapter  Google Scholar 

  15. Ting, I.H., Chi, H.M., Wu, J.S., Wang, S.L.: An approach for hate groups detection in facebook. In: Uden, L., Wang, L., Hong, T.P., Yang, H.C., Ting, I.H. (eds.) The 3rd International Workshop on Intelligent Data Analysis and Management, pp. 101–106. Springer, Netherlands (2013). doi:10.1007/978-94-007-7293-9_11

    Chapter  Google Scholar 

  16. Wei, Y., Singh, L., Martin, S.: Identification of extremism on twitter. In: International Conference on Advances in Social Networks Analysis and Mining (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Semantic Computing Group, CITEC, Bielefeld University, Bielefeld, Germany

    Matthias Hartung

  2. Semalytix GmbH, Bielefeld, Germany

    Matthias Hartung & Roman Klinger

  3. Institut für Maschinelle Sprachverarbeitung, University of Stuttgart, Stuttgart, Germany

    Roman Klinger

  4. Kompetenzzentrum Rechtsextremismus, Friedrich-Schiller-Universität Jena, Jena, Germany

    Franziska Schmidtke & Lars Vogel

Authors
  1. Matthias Hartung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Roman Klinger
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Franziska Schmidtke
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lars Vogel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthias Hartung .

Editor information

Editors and Affiliations

  1. Erasmus University Rotterdam, Rotterdam, The Netherlands

    Flavius Frasincar

  2. University of Liège , Liège, Belgium

    Ashwin Ittoo

  3. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Le Minh Nguyen

  4. Conservatoire National des Arts et Métiers, Paris, France

    Elisabeth Métais

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Hartung, M., Klinger, R., Schmidtke, F., Vogel, L. (2017). Identifying Right-Wing Extremism in German Twitter Profiles: A Classification Approach. In: Frasincar, F., Ittoo, A., Nguyen, L., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2017. Lecture Notes in Computer Science(), vol 10260. Springer, Cham. https://doi.org/10.1007/978-3-319-59569-6_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59569-6_40

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59568-9

  • Online ISBN: 978-3-319-59569-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation