IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/yfzsh.html
   My bibliography  Save this paper

Rhetorics of Radicalism

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://osf.io/download/5cb6e4dd3992690017126cbc/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/yfzsh?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Minwoo Ahn & Raksha Balakrishna & Michael Simeone & Marco A. Janssen, 2024. "When does group chat promote cooperation in shared resource governance?," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michal Ovádek & Nicolas Lampach & Arthur Dyevre, 2020. "What’s the talk in Brussels? Leveraging daily news coverage to measure issue attention in the European Union," European Union Politics, , vol. 21(2), pages 204-232, June.
    2. Dehler-Holland, Joris & Schumacher, Kira & Fichtner, Wolf, 2021. "Topic Modeling Uncovers Shifts in Media Framing of the German Renewable Energy Act," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 2(1).
    3. Mohamed M. Mostafa, 2023. "A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3905-3935, August.
    4. Zhang, Han, 2021. "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv 453jk, Center for Open Science.
    5. Ferrara, Federico M. & Masciandaro, Donato & Moschella, Manuela & Romelli, Davide, 2022. "Political voice on monetary policy: Evidence from the parliamentary hearings of the European Central Bank," European Journal of Political Economy, Elsevier, vol. 74(C).
    6. Dehler-Holland, Joris & Okoh, Marvin & Keles, Dogan, 2022. "Assessing technology legitimacy with topic models and sentiment analysis – The case of wind power in Germany," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. Seraphine F. Maerz & Carsten Q. Schneider, 2020. "Comparing public communication in democracies and autocracies: automated text analyses of speeches by heads of government," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 517-545, April.
    8. LIM Jaehwan & ITO Asei & ZHANG Hongyong, 2023. "Policy Agenda and Trajectory of the Xi Jinping Administration: Textual Evidence from 2012 to 2022," Policy Discussion Papers 23008, Research Institute of Economy, Trade and Industry (RIETI).
    9. Camilla Salvatore & Silvia Biffignandi & Annamaria Bianchi, 2022. "Corporate Social Responsibility Activities Through Twitter: From Topic Model Analysis to Indexes Measuring Communication Characteristics," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1217-1248, December.
    10. Ulrich Fritsche & Johannes Puckelwald, 2018. "Deciphering Professional Forecasters’ Stories - Analyzing a Corpus of Textual Predictions for the German Economy," Macroeconomics and Finance Series 201804, University of Hamburg, Department of Socioeconomics.
    11. Hager, Anselm & Hilbig, Hanno, 2020. "Does Public Opinion Affect Political Speech?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 64(4), pages 921-937.
    12. Peter Grajzl & Peter Murrell, 2021. "Characterizing a legal–intellectual culture: Bacon, Coke, and seventeenth-century England," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 15(1), pages 43-88, January.
    13. Peter Grajzl & Cindy Irby, 2019. "Reflections on study abroad: a computational linguistics approach," Journal of Computational Social Science, Springer, vol. 2(2), pages 151-181, July.
    14. Greene, Zac & Ceron, Andrea & Schumacher, Gijs & Fazekas, Zoltan, 2016. "The Nuts and Bolts of Automated Text Analysis. Comparing Different Document Pre-Processing Techniques in Four Countries," OSF Preprints ghxj8, Center for Open Science.
    15. Bastiaan Bruinsma & Moa Johansson, 2024. "Finding the structure of parliamentary motions in the Swedish Riksdag 1971–2015," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(4), pages 3275-3301, August.
    16. Keith Carlson & Michael A. Livermore & Daniel N. Rockmore, 2020. "The Problem of Data Bias in the Pool of Published U.S. Appellate Court Opinions," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(2), pages 224-261, June.
    17. Sara Kahn-Nisser, 2019. "When the targets are members and donors: Analyzing inter-governmental organizations’ human rights shaming," The Review of International Organizations, Springer, vol. 14(3), pages 431-451, September.
    18. Howoldt, David, 2024. "Characterising innovation policy mixes in innovation systems," Research Policy, Elsevier, vol. 53(2).
    19. Justyna Klejdysz & Robin L. Lumsdaine, 2023. "Shifts in ECB Communication: A Textual Analysis of the Press Conference," International Journal of Central Banking, International Journal of Central Banking, vol. 19(2), pages 473-542, June.
    20. Ebadi, Ashkan & Tremblay, Stéphane & Goutte, Cyril & Schiffauerova, Andrea, 2020. "Application of machine learning techniques to assess the trends and alignment of the funded research output," Journal of Informetrics, Elsevier, vol. 14(2).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:socarx:yfzsh. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://arabixiv.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.