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

Hartung M, Klinger R, Schmidtke F, Vogel L (2017)
In: Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems (NLDB 2017). Frascinar F, Ittoo A, Nguyen LM, Métais E (Eds); Lecture Notes in Computer Science, 10260. Springer International Publishing: 320-325.

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Book Chapter | Published | English
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Frascinar, Flavius ; Ittoo, Ashwin ; Nguyen, Le Minh ; Métais, Elisabeth
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.
Publishing Year
Conference
22nd International Conference on Natural Language & Information Systems (NLDB 2017)
Location
Liège, Belgium
Conference Date
2017-06-21 – 2017-06-23
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Hartung M, Klinger R, Schmidtke F, Vogel L. Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approach. In: Frascinar F, Ittoo A, Nguyen LM, Métais E, eds. Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems (NLDB 2017). Lecture Notes in Computer Science. Vol 10260. Springer International Publishing; 2017: 320-325.
Hartung, M., Klinger, R., Schmidtke, F., & Vogel, L. (2017). Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approach. In F. Frascinar, A. Ittoo, L. M. Nguyen, & E. Métais (Eds.), Lecture Notes in Computer Science: Vol. 10260. Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems (NLDB 2017) (pp. 320-325). Springer International Publishing.
Hartung, M., Klinger, R., Schmidtke, F., and Vogel, L. (2017). “Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approach” in Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems (NLDB 2017), Frascinar, F., Ittoo, A., Nguyen, L. M., and Métais, E. eds. Lecture Notes in Computer Science, vol. 10260, (Springer International Publishing), 320-325.
Hartung, M., et al., 2017. Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approach. In F. Frascinar, et al., eds. Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems (NLDB 2017). Lecture Notes in Computer Science. no.10260 Springer International Publishing, pp. 320-325.
M. Hartung, et al., “Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approach”, Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems (NLDB 2017), F. Frascinar, et al., eds., Lecture Notes in Computer Science, vol. 10260, Springer International Publishing, 2017, pp.320-325.
Hartung, M., Klinger, R., Schmidtke, F., Vogel, L.: Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approach. In: Frascinar, F., Ittoo, A., Nguyen, L.M., and Métais, E. (eds.) Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems (NLDB 2017). Lecture Notes in Computer Science. 10260, p. 320-325. Springer International Publishing (2017).
Hartung, Matthias, Klinger, Roman, Schmidtke, Franziska, and Vogel, Lars. “Identifying Right-Wing Extremism in German Twitter Profiles: a Classification Approach”. Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems (NLDB 2017). Ed. Flavius Frascinar, Ashwin Ittoo, Le Minh Nguyen, and Elisabeth Métais. Springer International Publishing, 2017.Vol. 10260. Lecture Notes in Computer Science. 320-325.
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