Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
John, Peter
2016.
The Political Science of British Politics: Representation and Accountability in a Westminster System.
SSRN Electronic Journal,
Henderson, John A.
2016.
An Experimental Approach to Measuring Ideological Positions in Political Text.
SSRN Electronic Journal ,
Denny, Matthew James
and
Spirling, Arthur
2017.
Text Preprocessing For Unsupervised Learning: Why It Matters, When It Misleads, And What To Do About It.
SSRN Electronic Journal ,
Wilkerson, John
and
Casas, Andreu
2017.
Large-Scale Computerized Text Analysis in Political Science: Opportunities and Challenges.
Annual Review of Political Science,
Vol. 20,
Issue. 1,
p.
529.
Broniecki, Philipp
and
Hanchar, Anna
2017.
Data innovation for international development: An overview of natural language processing for qualitative data analysis.
p.
92.
Kirkland, Justin H.
and
Slapin, Jonathan B.
2018.
Roll Call Rebels.
Kellstedt, Paul M.
and
Whitten, Guy D.
2018.
The Fundamentals of Political Science Research.
Peterson, Andrew
and
Spirling, Arthur
2018.
Classification Accuracy as a Substantive Quantity of Interest: Measuring Polarization in Westminster Systems.
Political Analysis,
Vol. 26,
Issue. 1,
p.
120.
Weaver, Iain S.
Williams, Hywel
Cioroianu, Iulia
Williams, Matthew
Coan, Travis
and
Banducci, Susan
2018.
Dynamic social media affiliations among UK politicians.
Social Networks,
Vol. 54,
Issue. ,
p.
132.
Lapponi, Emanuele
Søyland, Martin G.
Velldal, Erik
and
Oepen, Stephan
2018.
The Talk of Norway: a richly annotated corpus of the Norwegian parliament, 1998–2016.
Language Resources and Evaluation,
Vol. 52,
Issue. 3,
p.
873.
Cerrato, Andrea
Ferrara, Federico Maria
and
Ruggieri, Francesco
2018.
Why Does Import Competition Favor Republicans? Localized Trade Shocks, Voting Behavior, and Scapegoating in the U.S..
SSRN Electronic Journal ,
Temporão, Mickael
Vande Kerckhove, Corentin
van der Linden, Clifton
Dufresne, Yannick
and
Hendrickx, Julien M.
2018.
Ideological Scaling of Social Media Users: A Dynamic Lexicon Approach.
Political Analysis,
Vol. 26,
Issue. 4,
p.
457.
WESCHLE, SIMON
2018.
Quantifying Political Relationships.
American Political Science Review,
Vol. 112,
Issue. 4,
p.
1090.
Bonica, Adam
2018.
Inferring Roll‐Call Scores from Campaign Contributions Using Supervised Machine Learning.
American Journal of Political Science,
Vol. 62,
Issue. 4,
p.
830.
Denny, Matthew J.
and
Spirling, Arthur
2018.
Text Preprocessing For Unsupervised Learning: Why It Matters, When It Misleads, And What To Do About It.
Political Analysis,
Vol. 26,
Issue. 2,
p.
168.
Tzelgov, Eitan
and
Olander, Petrus
2018.
Economic Decline and Extreme‐Right Electoral Threat: How District‐Level Factors Shape the Legislative Debate on Immigration.
Legislative Studies Quarterly,
Vol. 43,
Issue. 4,
p.
649.
SLAPIN, JONATHAN B.
KIRKLAND, JUSTIN H.
LAZZARO, JOSEPH A.
LESLIE, PATRICK A.
and
O’GRADY, TOM
2018.
Ideology, Grandstanding, and Strategic Party Disloyalty in the British Parliament.
American Political Science Review,
Vol. 112,
Issue. 1,
p.
15.
Proksch, Sven-Oliver
2018.
Handbuch Methoden der Politikwissenschaft.
p.
1.
Goet, Niels D.
2019.
Measuring Polarization with Text Analysis: Evidence from the UK House of Commons, 1811–2015.
Political Analysis,
Vol. 27,
Issue. 4,
p.
518.
Bayram, Ulya
Pestian, John
Santel, Daniel
and
Minai, Ali A.
2019.
What’s in a Word? Detecting Partisan Affiliation from Word Use in Congressional Speeches.
p.
1.