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Computational Social Science
Big Data, Social Media, and Protest: Foundations for a Research Agenda
edited_book
Author(s):
Joshua A. Tucker
,
Jonathan Nagler
,
Megan Macduffee Metzger
,
Pablo Barberá
,
Duncan Penfold-Brown
,
Richard Bonneau
Editor(s):
R. Michael Alvarez
Publication date
(Online):
2016
Publisher:
Cambridge University Press
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Related collections
Annual Reviews Racial Justice, Policing, and Protest
Author and book information
Book Chapter
Pages
: 199-224
DOI:
10.1017/CBO9781316257340.009
SO-VID:
8803a55b-24f5-462f-aadd-81731ca8986e
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Book chapters
pp. vii
Preface
pp. 1
Introduction
pp. 27
The Application of Big Data in Surveys to the Study of Elections, Public Opinion, and Representation
pp. 51
Navigating the Local Modes of Big Data: The Case of Topic Models
pp. 98
Generating Political Event Data in Near Real Time: Opportunities and Challenges
pp. 121
Network Structure and Social Outcomes: Network Analysis for Social Science
pp. 140
Ideological Salience in Multiple Dimensions
pp. 168
Random Forests and Fuzzy Forests in Biomedical Research
pp. 199
Big Data, Social Media, and Protest: Foundations for a Research Agenda
pp. 225
Measuring Representational Style in the House: The Tea Party, Obama, and Legislators’ Changing Expressed Priorities
pp. 246
Using Social Marketing and Data Science to Make Government Smarter
pp. 266
Using Machine Learning Algorithms to Detect Election Fraud
pp. 295
Centralized Analysis of Local Data, with Dollars and Lives on the Line: Lessons from the Home Radon Experience
pp. 307
Computational Social Science: Toward a Collaborative Future
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