Special Issue: Applied Quantitative Text Analysis

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Romanian Journal of Political Science, Vol. 20, no. 2, Winter 2020

For social scientists in general, and political scientists in particular, text has always been a resource of reference. In an increasingly overflooded world with written text and with welcome advances in computer-assisted techniques to analyze it, researchers have now at their disposal the conceptual, analytical and visual tools to systematically extract meaning from political text for social scientific purposes.

The Romanian Journal of Political Science opens a Call for Papers for a Special Issue on Applied Quantitative Text Analysis, looking for original contributions of substantive and methodological papers using various forms of quantitative text analysis applied to relevant political science questions.

Papers applying various text analysis methods include the following:

  • classical content analysis methods
  • dictionary-based methods
  • classification and machine learning methods
  • scaling methods
  • topic models
  • qualitative techniques of human coding and annotation for the purposes of validation for automated approaches

Papers problematizing fundamental issues of quantitative text analysis are encouraged, on topics such as inter-coder agreement, reliability, validation, accuracy, and precision.

Applications of quantitative analyses to substantive political science problems are encouraged. Examples of topics include, but are not limited to, the following:

  • social media analysis of relevant political issues
  • analysis of political speeches
  • impact of political issues through newspapers
  • gradients of political ideology
  • policy positions and preferences
  • classifications of populist speeches
  • estimating voting behavior from online presence

The deadline for submission is January 31st, 2020. All submitted manuscripts will go through double blind peer review. Decisions on accepted manuscripts will be made no later than June 2020. The Special Issue will be published in Winter 2020.

Guest Editors

Zoltán Fazekas

Iulia Cioroianu

Daniela Crăciun

About the Journal

The Romanian Journal of Political Science (PolSci) is the first peer-review Romanian political science journal, edited and published twice a year by the Romanian Academic Society (SAR). The journal publishes a diverse range of political science articles, especially from fields currently under-covered, such as comparative politics, public policy, political economy, or political psychology. Papers are theory-grounded and based on solid empirical work. PolSci is in accreditation with the Social Science Citation Index. According to ISI Web of Knowledge, PolSci’s 5 Year Impact Factor was 0,246.

About Guest Editors

Zoltán Fazekas is Associate Professor of Business and Politics, with focus on quantitative methods in the Department of International Economics, Government and Business at the Copenhagen Business School. Zoltán holds a Ph.D. in Political Science from the University of Vienna (2012) and his research is broadly at the intersection of political psychology, political communication, and comparative politics. He studies political attitude formation, the role and content of political coverage, and the interaction between political elites and the public. His work has been published, among others, in the American Journal of Political Science, Journal of Communication, British Journal of Political Science, and Political Psychology. His methodological interests and expertise lie in hierarchical modeling, quantitative text analysis, and computational tools for social sciences.

Iulia Cioroianu is a Prize Fellow in the Institute for Policy Research at the University of Bath. She holds a Ph.D. in Political Science from New York University and an M.A. from Central European University. Before joining the IPR, she was a research fellow in the Q-Step Centre for Quantitative Social Sciences at the University of Exeter, and a pre-doctoral fellow in the LSE Department of Methodology. Iulia is a social data scientist who studies the effects of social media and online information exposure on political competition and polarization, using natural language processing, quantitative text analysis, machine learning and survey experiments. Her work has been funded by IBM and the UK Economic and Social Research Council and has been published in political science and computer science journals and conference proceedings and featured in Sage and NCRM podcasts and research methods videos.

Daniela Crăciun is Lecturer at Bard College Berlin (Germany). She earned a Ph.D. in Political Science from Central European University, an Erasmus Mundus M.A. in Global Studies from the University of Leipzig (Germany), Jawaharlal Nehru University (India) and Wroclaw University (Poland), and a B.A. in Marketing with Media and Cultural Studies from Canterbury Christ Church University (UK). Daniela’s research interests lie in the areas of research design, conceptualization and content analysis. Her Ph.D. dissertation analyzed national higher education internationalization strategies from around the world using computer-assisted text analysis to lift empirical data to a conceptual level. Daniela has been a Visiting Scholar doing research or teaching at the University of Yangon (Myanmar), the Federal University of Sao Carlos (Brazil), and the Center for International Higher Education at Boston College (USA). Her postdoctoral research explores issues of graduate employability.

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