IDEAS home Printed from https://ideas.repec.org/a/bpj/soeuro/v70y2022i1p24-46n7.html
   My bibliography  Save this article

The “Digital Turn” in Transitional Justice Research: Evaluating Image and Text as Data in the Western Balkans

Author

Listed:
  • Kostovicova Denisa

    (European Institute, London School of Economics and Political Science, London, UK)

  • Kerr Rachel

    (Department of War Studies, King’s College, London, UK)

  • Sokolić Ivor

    (School of Humanities, University of Hertfordshire, Hatfield, UK)

  • Fairey Tiffany

    (Department of War Studies, King’s College, London, UK)

  • Redwood Henry

    (London South Bank University, London, UK)

  • Subotić Jelena

    (Department of Political Science, Georgia State University, Atlanta, GA, USA)

Abstract

The “digital turn” has transformed the landscape of transitional justice research. A wealth of data has been created through social media channels, and new digitisation tools have made existing data more easily accessible. This article discusses the ethical and methodological dimensions of using digital data and novel technologies in transitional justice research based on innovative research using digital archives, digitised transcripts, social media (Facebook) content and digital images. The authors review and evaluate how, in each of these domains, new digital technologies have enabled scholars to expand empirical evidence to understand the mechanics of transitional justice by analysing how data is produced and curated, to interrogate ethical dilemmas involved in those processes and to shift the focus from the ability of transitional justice to fulfil normative goals to how transitional justice is enacted and articulated as a process.

Suggested Citation

  • Kostovicova Denisa & Kerr Rachel & Sokolić Ivor & Fairey Tiffany & Redwood Henry & Subotić Jelena, 2022. "The “Digital Turn” in Transitional Justice Research: Evaluating Image and Text as Data in the Western Balkans," Comparative Southeast European Studies, De Gruyter, vol. 70(1), pages 24-46, March.
    • Handle: RePEc:bpj:soeuro:v:70:y:2022:i:1:p:24-46:n:7
    DOI: 10.1515/soeu-2021-0055
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/soeu-2021-0055
    Download Restriction: no
    File URL: https://libkey.io/10.1515/soeu-2021-0055?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. Mueller, Hannes & Rauh, Christopher, 2018. "Reading Between the Lines: Prediction of Political Violence Using Newspaper Text," American Political Science Review, Cambridge University Press, vol. 112(2), pages 358-375, May.
    3. Benoit, Kenneth & Conway, Drew & Lauderdale, Benjamin E. & Laver, Michael & Mikhaylov, Slava, 2016. "Crowd-sourced Text Analysis: Reproducible and Agile Production of Political Data," American Political Science Review, Cambridge University Press, vol. 110(2), pages 278-295, May.
    4. Laver, Michael & Benoit, Kenneth & Garry, John, 2003. "Extracting Policy Positions from Political Texts Using Words as Data," American Political Science Review, Cambridge University Press, vol. 97(2), pages 311-331, May.
    5. Michael Evans & Wayne McIntosh & Jimmy Lin & Cynthia Cates, 2007. "Recounting the Courts? Applying Automated Content Analysis to Enhance Empirical Legal Research," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 4(4), pages 1007-1039, December.
    6. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    Full references (including those not matched with items on IDEAS)

    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. Martin Haselmayer & Marcelo Jenny, 2017. "Sentiment analysis of political communication: combining a dictionary approach with crowdcoding," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2623-2646, November.
    2. H. Andrew Schwartz & Lyle H. Ungar, 2015. "Data-Driven Content Analysis of Social Media," The ANNALS of the American Academy of Political and Social Science, , vol. 659(1), pages 78-94, May.
    3. Anton Oleinik, 2024. "A Bayesian index of association: comparison with other measures and performance," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 277-305, February.
    4. Rybinski, Krzysztof, 2020. "The forecasting power of the multi-language narrative of sell-side research: A machine learning evaluation," Finance Research Letters, Elsevier, vol. 34(C).
    5. Weiss, Max & Zoorob, Michael, 2021. "Political frames of public health crises: Discussing the opioid epidemic in the US Congress," Social Science & Medicine, Elsevier, vol. 281(C).
    6. Mihalyi, David & Mate, Akos, 2019. "Text-mining IMF country reports - an original dataset," MPRA Paper 100656, University Library of Munich, Germany.
    7. Sarel, Roee & Demirtas, Melanie, 2021. "Delegation in a multi-tier court system: Are remands in the U.S. federal courts driven by moral hazard?," European Journal of Political Economy, Elsevier, vol. 68(C).
    8. Pierre-Marc Daigneault & Dominic Duval & Louis M. Imbeau, 2018. "Supervised scaling of semi-structured interview transcripts to characterize the ideology of a social policy reform," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(5), pages 2151-2162, September.
    9. Diaf, Sami & Döpke, Jörg & Fritsche, Ulrich & Rockenbach, Ida, 2022. "Sharks and minnows in a shoal of words: Measuring latent ideological positions based on text mining techniques," European Journal of Political Economy, Elsevier, vol. 75(C).
    10. Miriam Sorace, 2018. "The European Union democratic deficit: Substantive representation in the European Parliament at the input stage," European Union Politics, , vol. 19(1), pages 3-24, March.
    11. Soojin Oh Park & Nail Hassairi, 2021. "What predicts legislative success of early care and education policies?: Applications of machine learning and Natural Language Processing in a cross-state early childhood policy analysis," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-36, February.
    12. Heike Klüver, 2015. "The promises of quantitative text analysis in interest group research: A reply to Bunea and Ibenskas," European Union Politics, , vol. 16(3), pages 456-466, September.
    13. Merz, Nicolas & Regel, Sven & Lewandowski, Jirka, 2016. "The Manifesto Corpus: A new resource for research on political parties and quantitative text analysis," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 3(2 (April-), pages 1-8.
    14. 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.
    15. H Andrew Schwartz & Johannes C Eichstaedt & Margaret L Kern & Lukasz Dziurzynski & Stephanie M Ramones & Megha Agrawal & Achal Shah & Michal Kosinski & David Stillwell & Martin E P Seligman & Lyle H U, 2013. "Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-16, September.
    16. Keren Weinshall & Lee Epstein, 2020. "Developing High‐Quality Data Infrastructure for Legal Analytics: Introducing the Israeli Supreme Court Database," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(2), pages 416-434, June.
    17. Stefano Pagliari & Meredith Wilf, 2021. "Regulatory novelty after financial crises: Evidence from international banking and securities standards, 1975–2016," Regulation & Governance, John Wiley & Sons, vol. 15(3), pages 933-951, July.
    18. Elio Amicarelli & Jessica Di Salvatore, 2021. "Introducing the PeaceKeeping Operations Corpus (PKOC)," Journal of Peace Research, Peace Research Institute Oslo, vol. 58(5), pages 1137-1148, September.
    19. Rebecca Cordell & Kristian Skrede Gleditsch & Florian G Kern & Laura Saavedra-Lux, 2020. "Measuring institutional variation across American Indian constitutions using automated content analysis," Journal of Peace Research, Peace Research Institute Oslo, vol. 57(6), pages 777-788, November.
    20. Born, Andreas & Janssen, Aljoscha, 2022. "Does a district mandate matter for the behavior of politicians? An analysis of roll-call votes and parliamentary speeches," European Journal of Political Economy, Elsevier, vol. 71(C).

    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:bpj:soeuro:v:70:y:2022:i:1:p:24-46:n:7. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.