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Rhetorics of Radicalism

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  • Karell, Daniel
  • Freedman, Michael Raphael

Abstract

What rhetorics run throughout radical discourse, and why do some gain prominence over others? The scholarship on radicalism largely portrays radical discourse as opposition to powerful ideas and enemies, but radicals often evince great interest in personal and local concerns. To shed light on how radicals use and adopt rhetoric, we analyze an original corpus of more than 23,000 pages produced by Afghan radical groups between 1979 and 2001 using a novel computational abductive approach. We first identify how radicalism not only attacks dominant ideas, actors, and institutions using a rhetoric of subversion, but also how it can use a rhetoric of reversion to urge intimate transformations in morals and behavior. Next, we find evidence that radicals’ networks of support affect the rhetorical mixture they espouse, due to social ties drawing radicals into encounters with backers’ social domains. Our study advances a relational understanding of radical discourse, while also showing how a combination of computational and abductive methods can help theorize and analyze discourses of contention.

Suggested Citation

  • Karell, Daniel & Freedman, Michael Raphael, 2019. "Rhetorics of Radicalism," SocArXiv yfzsh, Center for Open Science.
  • Handle: RePEc:osf:socarx:yfzsh
    DOI: 10.31219/osf.io/yfzsh
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    References listed on IDEAS

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    1. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    2. Denny, Matthew J. & Spirling, Arthur, 2018. "Text Preprocessing For Unsupervised Learning: Why It Matters, When It Misleads, And What To Do About It," Political Analysis, Cambridge University Press, vol. 26(2), pages 168-189, April.
    3. Matthew Isaacs, 2016. "Sacred violence or strategic faith? Disentangling the relationship between religion and violence in armed conflict," Journal of Peace Research, Peace Research Institute Oslo, vol. 53(2), pages 211-225, March.
    4. Papke, Leslie E & Wooldridge, Jeffrey M, 1996. "Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 619-632, Nov.-Dec..
    5. Lucas, Christopher & Nielsen, Richard A. & Roberts, Margaret E. & Stewart, Brandon M. & Storer, Alex & Tingley, Dustin, 2015. "Computer-Assisted Text Analysis for Comparative Politics," Political Analysis, Cambridge University Press, vol. 23(2), pages 254-277, April.
    6. Salehyan, Idean & Siroky, David & Wood, Reed M., 2014. "External Rebel Sponsorship and Civilian Abuse: A Principal-Agent Analysis of Wartime Atrocities," International Organization, Cambridge University Press, vol. 68(3), pages 633-661, July.
    7. Margaret E. Roberts & Brandon M. Stewart & Dustin Tingley & Christopher Lucas & Jetson Leder‐Luis & Shana Kushner Gadarian & Bethany Albertson & David G. Rand, 2014. "Structural Topic Models for Open‐Ended Survey Responses," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 1064-1082, October.
    8. Mitts, Tamar, 2019. "From Isolation to Radicalization: Anti-Muslim Hostility and Support for ISIS in the West," American Political Science Review, Cambridge University Press, vol. 113(1), pages 173-194, February.
    9. Rink, Anselm & Sharma, Kunaal, 2018. "The Determinants of Religious Radicalization: Evidence from Kenya," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 62(6), pages 1229-1261.
    10. Kevin M. Quinn & Burt L. Monroe & Michael Colaresi & Michael H. Crespin & Dragomir R. Radev, 2010. "How to Analyze Political Attention with Minimal Assumptions and Costs," American Journal of Political Science, John Wiley & Sons, vol. 54(1), pages 209-228, January.
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