Persönlicher Status und Werkzeuge

Academic Career and Research Areas

The research of Simon Hegelich (b. 1976) focuses on the connection between political science and data science. He is interested in the political dimension of the ongoing digital revolution as well as in implementing new methods in political science such as machine learning, data mining, computer vision and simulations.
Hegelich studied political science at the University of Münster (Germany), where he also received his doctorate and acquired his postdoctoral teaching qualification (habilitation). From 2011 to 2016, he was managing director of the interdisciplinary research center FoKoS of the University of Siegen. In 2016, Simon Hegelich was appointed associate professor at the Bavarian School of Public Policy.

Key Publications (all publications)

Hegelich S: “Decision trees and random forests: Machine learning techniques to classify rare events”. European Policy Analysis. 2016; 2(1): 98-120.

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Hegelich S, Fraune C, Knollmann D: “Point Predictions and the Punctuated Equilibrium Theory: A Data Mining Approach—U.S. Nuclear Policy as Proof of Concept”. Policy Studies Journal. 2015; 43(2): 228-256.

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Thieltges A, Schmidt F, Hegelich S: “The Devil‘s Triangle: Ethical considerations on developing bot detection methods”. AAAI. 2016 Spring Symposium, Technical Report, SS-2016; 16-01, 277-281.

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Grabau M, Hegelich S: “The Gas Game: Simulating Decision-Making in the European Union's External Natural Gas Policy (mit Martina Grabau)”. Swiss Political Science Review. 2016; 22(2): 232-263.

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Hegelich S, Shahrezaye M: “The Communication Behavior of German MPs on Twitter: Preaching to the Converted and Attacking Opponents”. European Policy Analysis (EPA). 2015; 1(2): 155-174.

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