"I’m known as a political scientist through my research and my background, but at heart I am a computational social scientist and quantitative methodologist. My primary interests over more than two decades of research and teaching are in quantitative and and computational methods for studying the social and political world."
- Dr Ken Benoit shares his research interests as part of our 30th Anniversary celebrations. Read the full close-up with Methodology faculty.
Ken Benoit is Director of the Data Science Institute at LSE and Professor of Computational Social Science in the Department of Methodology.
Ken’s current research focuses on computational, quantitative methods for processing large amounts of textual data, mainly political texts and social media. Current interest span from the analysis of big data, including social media, and methods of text mining. He has published extensively on applications of measurement and the analysis of text as data in political science, including machine learning methods and text coding through crowd-sourcing, an approach that combines statistical scaling with the qualitative power of thousands of human coders working in tandem on small coding tasks.
He received his PhD in Government with a specialisation in statistical methodology from Harvard University.
His substantive research interests include comparative party competition, the European Parliament, electoral systems, and transitions to democracy. Much of his recent work involves estimating the electoral effects of campaign spending. He is also a leading specialist on Hungarian elections and the Hungarian electoral system. His methodological interests include statistical methodologies for the social sciences, especially those relating to measurement and quantitative text analysis. Recent data large-scale measurement projects in which he has been involved include estimating policy positions of political parties through expert surveys, manifesto coding, and text analysis.
See Ken's Google Scholar page.