Howard Liu

Howard Liu

Assistant Professor
Department of Government

University of Essex

About me

Welcome! I am a Lecturer (Assistant Professor) in the Department of Government at the University of Essex.

In my research, I write about contentious politics, state repression, and armed conflict, with a particular attention to how network relationships shape conflict behavior. My research has been published at Journal of Politics and Political Science Research and Methods, among others.

Interests

  • Contentious Politics
  • State Repression
  • Armed Conflicts
  • Network Analysis

Education

  • PhD in Political Science, 2019

    Duke University

  • MS in Political Science, 2009

    National Taiwan University, Taiwan

  • BA in Diplomacy, 2007

    National Chengchi University, Taiwan

Publications

Elite Competition, Local Extraction, and Social Unrest: Understanding Mass Protest in Authoritarian Regimes

(2020). Published in Journal of Global Security Studies.
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Hierarchy and the provision of order in international politics

(2020). Published in The Journal of Politics.
Kyle Beardsley, Howard Liu, Peter Mucha, David Siegel, Juan Tellez
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Lost in Space: Geolocation in Event Data

(2019). Published in Political Science Research and Methods.
Sophie Lee, Howard Liu, Michael D. Ward
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Working Papers

Taking Dyads Seriously

Revise and Resubmit. Political Science Research and Methods.
Shahryar Minhas, Cassy Dorff, Margaret Foster, Max Gallop, Howard Liu, Juan Tellez, Michael D. Ward

And the Heat Goes On: Police Repression and the Modalities of Power

Revise and Resubmit. Journal of Conflict Resolution
Howard Liu, Christopher Sullivan

Who Leaves and Who Stays? Organizational Hierarchy and Rebel Fragmentation

Under Review.
Chuyu Liu, Howard Liu

Transportation Infrastructure and Rebel Crime in Civil Wars

Under Review.
Howard Liu, Juan Tellez

White Terror: Relational Punishment, Defection, and Demobilization of Underground Dissent Movements in Repressive Regimes

Under Review.

Teaching

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GV900 - Political Explanation

This module offers an introduction to the theory and practice of quantitative data analysis techniques.