David Muchlinski

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Sarah BirchKing's College LondonVerified email at kcl.ac.uk
David S. SirokyProfessor of International Relations, Department of Political Science, University of FloridaVerified email at ufl.edu
Matthew Adam KocherDepartment of Political Science and The School of Advanced International Studies, Johns HopkinsVerified email at jhu.edu
Jingrui HeUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Caleb ZiemsStanford UniversityVerified email at stanford.edu
Jordyn SeyboltTeachers College, Columbia UniversityVerified email at tc.columbia.edu
Mai ElSheriefAssistant Professor, Northeastern UniversityVerified email at northeastern.edu
Diyi YangStanford UniversityVerified email at stanford.edu
Munmun De ChoudhuryGeorgia Institute of TechnologyVerified email at gatech.edu
Benjamin E. GoldsmithProfessor, Australian National UniversityVerified email at anu.edu.au
Charles ButcherNorwegian University of Science and TechnologyVerified email at ntnu.no
Sascha NanlohyUniversity of SydneyVerified email at sydney.edu.au
Xiao YangAmazon, Inc.Verified email at amazon.com
Craig MacdonaldSchool of Computing Science, University of GlasgowVerified email at glasgow.ac.uk
Iadh OunisProfessor at the University of Glasgow, School of Computing ScienceVerified email at glasgow.ac.uk
Alfred KrzywickiUniversity of Adelaide, AustraliaVerified email at unsw.edu.au
Ben D. SawyerAssociate Professor of Industrial Engineering, University of Central FloridaVerified email at mit.edu
Matthew CanhamCEO, Beyond Layer Seven, LLCVerified email at belay7.com

David Muchlinski

Georgia Institute of Technology

Verified email at inta.gatech.edu - Homepage

Conflict forecasting Radicalization Computational Social Science Political Methodology


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Comparing random forest with logistic regression for predicting class-imbalanced civil war onset data D Muchlinski, D Siroky, J He, M Kocher Political Analysis 24 (1), 87-103, 2016	311	2016
Latent hatred: A benchmark for understanding implicit hate speech M ElSherief, C Ziems, D Muchlinski, V Anupindi, J Seybolt, ... arXiv preprint arXiv:2109.05322, 2021	142	2021
Electoral violence prevention: what works? S Birch, D Muchlinski Democratization 25 (3), 385-403, 2018	95	2018
The dataset of countries at risk of electoral violence S Birch, D Muchlinski Terrorism and political violence 32 (2), 217-236, 2020	87	2020
Introducing the targeted mass killing data set for the study and forecasting of mass atrocities C Butcher, BE Goldsmith, S Nanlohy, A Sowmya, D Muchlinski Journal of Conflict Resolution 64 (7-8), 1524-1547, 2020	47	2020
Grievances and opportunities: Religious violence across political regimes D Muchlinski Politics and Religion 7 (4), 684-705, 2014	36	2014
We need to go deeper: Measuring electoral violence using convolutional neural networks and social media I Muchlinski, David., Yang, Xiao., Birch, Sarah., Macdonald, Craig., & Ounis Political Science Research and Methods 9 (1), 122-139, 2021	34	2021
Electoral violence: Patterns and trends 1 S Birch, D Muchlinski Electoral integrity and political regimes, 100-112, 2017	19	2017
Seeing the forest through the trees DA Muchlinski, D Siroky, J He, MA Kocher Political Analysis 27 (1), 111-113, 2019	7	2019
Machine Learning and Deep Learning D Muchlinski Elgar Encycl. Technol. Polit, 114-118, 2022	3	2022
Swords and plowshares: Property rights, collective action, and nonstate governance in the Jewish community of Palestine 1920–1948 D Muchlinski American Political Science Review 115 (4), 1373-1387, 2021	3	2021
Swords and Plowshares Jewish non-Weberian Governance in British Palestine D Muchlinski Arizona State University, 2013	3	2013
Codebook for the Dataset of Countries at Risk for Electoral Violence (CREV) S Birch, D Muchlinski version, 2017	2	2017
From academia to policy makers: a methodology for real-time forecasting of infrequent events A Krzywicki, D Muchlinski, BE Goldsmith, A Sowmya Journal of Computational Social Science 5 (2), 1489-1510, 2022	1	2022
Machine learning and deep learning T Pei, S Sobolevsky, C Ratti, S Shaw, T Li Elgar Encyclopedia of Technology and Politics; Edward Elgar Publishing …, 2022	1	2022
Response to Kapoor and Narayanan M Muchlinski, David, Siroky, David, He, Jingrui, Kocher https://www.researchgate.net/publication …, 2022		2022
Understanding Online Information Operations: Development of an Influence Network for Scientific Inquiry Testing Environment (INSITE) C Crooks, T McNeil, B Sawyer, M Canham, D Muchlinski 2020 IEEE International Conference on Big Data (Big Data), 4318-4324, 2020		2020
The Politics and Effects of Religious Grievance D Muchlinski Oxford Research Encyclopedia of Politics, 2019		2019
6 Electoral violence S Birch, D Muchlinski Electoral Integrity and Political Regimes: Actors, Strategies and …, 2017		2017
Identity politics on the world stage D Muchlinski, D Siroky Encounters with World Affairs, 295-310, 2016		2016

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