Following the Trail of Words: Mapping the Trending Topics of Graduate Research in the Brazilian IR Scholarship (1987-2018)

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Abstract

This paper advances our understanding of the Brazilian IR scholarship by exploring the topics addressed and the geographic scope adopted by its authors, tracing their evolution over time. We utilize data from 2417 master’s theses and doctoral dissertations from all IR graduate programs in the country, spanning the years 1987 to 2018. By employing a structural topic model, we identify latent topics present in the abstracts of these documents. This analysis not only allows us to trace a thematic profile of the Brazilian IR scholarship but also provides evidence that the expansion of the Brazilian IR scholarship in the 2000s has led to 01. an increased diversity of topics explored by researchers, and 02. analyses with a broader geographic scope, extending beyond the immediate region. Therefore, as the Brazilian IR scholarship has consolidated, there has been a transition from a policy-oriented approach to a more active involvement in international debates across different subjects and regions.

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Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts

Justin Grimmer, Brandon M. Stewart (2013)

Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have hindered their use in political science research. Here lies the promise of automated text analysis: it substantially reduces the costs of analyzing large collections of text. We provide a guide to this exciting new area of research and show how, in many instances, the methods have already obtained part of their promise. But there are pitfalls to using automated methods—they are no substitute for careful thought and close reading and require extensive and problem-specific validation. We survey a wide range of new methods, provide guidance on how to validate the output of the models, and clarify misconceptions and errors in the literature. To conclude, we argue that for automated text methods to become a standard tool for political scientists, methodologists must contribute new methods and new methods of validation.