Abstract
Online propaganda is central to the recruitment strategies of extremist groups and in recent years these efforts have increasingly extended to women. To investigate Islamic State’s approach to targeting women in their online propaganda and uncover implications for counterterrorism, we rely on text mining and natural language processing (NLP). Specifically, we extract articles published in Dabiq and Rumiyah (Islamic State’s online English language publications) to identify prominent topics. To identify similarities or differences between these texts and those produced by non-violent religious groups, we extend the analysis to articles from a Catholic forum dedicated to women. We also perform an emotional analysis of both of these resources to better understand the emotional components of propaganda. We rely on Depechemood (a lexical-base emotion analysis method) to detect emotions most likely to be evoked in readers of these materials. The findings indicate that the emotional appeal of ISIS and Catholic materials are similar.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aggarwal, C.C.: Machine Learning for Text. Springer, Heidelberg (2018)
Aymenn Jawad Al-Tamimi: The dawn of the islamic state of iraq and ash-sham. Curr. Trends Islamist Ideol. 16, 5 (2014)
Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)
Bodine-Baron, E., Helmus, T.C., Magnuson, M., Winkelman, Z.: Examining ISIS support and opposition networks on twitter. Technical report, RAND Corporation Santa Monica United States (2016)
Canales, L., Martínez-Barco, P.: Emotion detection from text: A survey. In: Proceedings of the Workshop on Natural Language Processing in the 5th Information Systems Research Working Days, JISIC, pp. 37–43 (2014)
Farwell, J.P.: The media strategy of ISIS. Survival 56(6), 49–55 (2014)
Gates, S., Podder, S.: Social media, recruitment, allegiance and the Islamic state. Perspect. Terrorism 9(4), 107–116 (2015)
Ingram, H.J.: An analysis of inspire and Dabiq: Lessons from AQAP and Islamic state’s propaganda war. Stud. Confl. Terrorism 40(5), 357–375 (2017)
Kneip, K.: Female jihad–women in the ISIS. Politikon 29, 88–106 (2016)
Kowsari, K., Jafari Meimandi, K., Heidarysafa, M., Mendu, S., Barnes, L., Brown, D.: Text classification algorithms: a survey. Information 10(4), 150 (2019)
Kuang, D., Brantingham, P.J., Bertozzi, A.L.: Crime topic modeling. Crime Sci. 6(1), 12 (2017)
Laub, Z., Masters, J.: Islamic state in Iraq and greater Syria. The Council on Foreign Relations (2014)
Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401(6755), 788 (1999)
Callaghan, D., Greene, D., Carthy, J., Cunningham, P.: An analysis of the coherence of descriptors in topic modeling. Expert Syst. Appl. 42(13), 5645–5657 (2015)
Perešin, A.: Fatal attraction: western muslimas and isis. Perspect. Terror. 9(3), 21–38 (2015)
Plutchik, R.: A general psychoevolutionary theory of emotion. In: Plutchik, R., Kellerman, H. (eds.) Theories of Emotion, pp. 3–33. Academic Press, Cambridge (1980)
Plutchik, R.: The nature of emotions: Human emotions have deep evolutionary roots, a fact that may explain their complexity and provide tools for clinical practice. Am. Sci. 89(4), 344–350 (2001)
Rowe, M., Saif, H.: Mining pro-ISIS radicalisation signals from social media users. In: Tenth International AAAI Conference on Web and Social Media (2016)
Saif, H., Fernández, M., He, Y., Alani, H.: On stopwords, filtering and data sparsity for sentiment analysis of twitter (2014)
Jones, K.S.: A statistical interpretation of term specificity and its application in retrieval. J. Doc. 28(1), 11–21 (1972)
Staiano, J., Guerini, M.: Depechemood: a lexicon for emotion analysis from crowd-annotated news. arXiv preprintarXiv:1405.1605 (2014)
Tokunaga, T., Makoto, I.: Text categorization based on weighted inverse document frequency. In: Special Interest Groups and Information Process Society of Japan (SIG-IPSJ. Citeseer (1994)
Vergani, M., Bliuc, A.M.: The evolution of the ISIS’language: a quantitative analysis of the language of the first year of Dabiq magazine. Sicurezza, Terrorismo e Società = Secur. Terror. Soc. 2(2), 7–20 (2015)
Verma, T., Renu, R., Gaur, D.: Tokenization and filtering process in rapidminer. Int. J. Appl. Inf. Syst. 7(2), 16–18 (2014)
Wignell, P., Tan, S., O’Halloran, K., Lange, R.: A mixed methods empirical examination of changes in emphasis and style in the extremist magazines dabiq and rumiyah. Perspect. Terror. 11(2), 2–20 (2017)
Winter, C.: The Virtual ‘Caliphate’: Understanding Islamic State’s Propaganda Strategy, vol. 25. Quilliam, London (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Heidarysafa, M., Kowsari, K., Odukoya, T., Potter, P., Barnes, L.E., Brown, D.E. (2020). Women in ISIS Propaganda: A Natural Language Processing Analysis of Topics and Emotions in a Comparison with a Mainstream Religious Group. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1229. Springer, Cham. https://doi.org/10.1007/978-3-030-52246-9_45
Download citation
DOI: https://doi.org/10.1007/978-3-030-52246-9_45
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-52245-2
Online ISBN: 978-3-030-52246-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)