Bias in Text Analysis for International Relations Research

Abstract

Abstract How international is political text-analysis research? In computational text analysis, corpus selection skews heavily toward English-language sources and reflects a Western bias that influences the scope, interpretation, and generalizability of research on international politics. For example, corpus selection bias can affect our understanding of alliances and alignments, internal dynamics of authoritarian regimes, durability of treaties, the onset of genocide, and the formation and dissolution of non-state actor groups. Yet, there are issues along the entire “value chain” of corpus production that affect research outcomes and the conclusions we draw about things in the world. I identify three issues in the data-generating process pertaining to discourse analysis of political phenomena: information deficiencies that lead to corpus selection and analysis bias; problems regarding document preparation, such as the availability and quality of corpora from non-English sources; and gaps in the linguist analysis pipeline. Short-term interventions for incentivizing this agenda include special journal issues, conference workshops, and mentoring and training students in international relations in this methodology. Longer term solutions to these issues include promoting multidisciplinary collaboration, training students in computational discourse methods, promoting foreign language proficiency, and co-authorship across global regions that may help scholars to learn more about global problems through primary documents.