Global Knowledge Structures: International Patterns of Language Adoption in Political Science

• In Event: 067 - Section on Science, Knowledge and Technology Roundtables (one-hour)
  In Refereed Roundtable: Table 04. Paradigms and People

Abstract

Many scholars believe research is generated independently of “place,” specifically the nation-state. What if this were incorrect and especially for political science? We argue that the characteristics of nation-states significantly describe the research topics that political scientists pursue over time. Drawing from computational linguistics, we apply topic model (latent Dirichlet allocation) techniques to over 60,000 political science papers (1991-2011) present in the Reuters’s Web of Science corpus so as to identify sets of words uniquely associated with each nation-state. With this information, we are able to identify how similar the political science vocabularies of two nations are over time. In addition, we are able to identify whether the papers generated in one nation-state draw on the vocabularies characteristic of other nation-states, or global language borrowing. By combining this information with nation level characteristics, we test whether political, economic, and cultural differences between nation-states correspond with their patterns of language similarity and borrowing.

Authors

• Charles Jonathan Gomez, Stanford University

• Daniel A. McFarland, Stanford University