"The Use of NLP for Data Creation and Analysis in Political Science: Computational Text Analysis using Newspapers and Legislation Documents"

by Ashrakat Elshehawy, University of Oxford

Update: the event has now finished (Apr 27th 2022).

Abstract

In recent decades, governments have started to maintain an online presence of their archives and documentation of their proceedings and decisions. Newspapers around the world continue to produce daily textual data. Different groups and individuals are also employing online platforms at a rapid rate, like Twitter, Facebook, and Reddit, that constantly store data about users’ activities. All of this has led to an availability of extensive text data online that social scientists can make use of to answer pressing research questions that were previously difficult to approach. In this talk, I speak about the applications of Text as Data in the field of political science. Specifically, I focus on two types of text as data, newspaper articles and US legislation. The talk discusses a recent publication that uses NLP and text analysis on over one million news articles to identify the prevalence of Russian illiberal discourse and its timing relative to German elections. The talk also underlines how NLP and computational text analysis methods are used on US legislation to build a dataset about economic sanctions that improves coverage of US sanction cases from previous datasets.

Speaker’s bio

Ashrakat Elshehawy is a visiting PhD student at Yale University and a doctoral student at the Department of Politics and International Relations at the University of Oxford. Her research interests lie in the field of comparative political economy. Her research draws on questions related to the politics of public service provision and the politics of information. In her recent publications, she has focused on how foreign policy tools, such as economic sanctions, interact with domestic politics and how the NLP techniques can be used to analyse them. She has authored several journal publications related to digital humanities, including “SASCAT: Natural Language Processing Approach to the Study of Economic Sanctions” and “Illiberal Communication and Election Intervention during the Refugee Crisis in Germany”. She also taught several courses at the graduate level on Applied Statistics, Python, and Computational Text Analysis.

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