Abstract is missing.
- PrefaceGary King. [doi]
- IntroductionR. Michael Alvarez. 1-24 [doi]
- The Application of Big Data in Surveys to the Study of Elections, Public Opinion, and RepresentationChristopher Warshaw. 27-50 [doi]
- Navigating the Local Modes of Big Data: The Case of Topic ModelsMargaret E. Roberts, Brandon M. Stewart, Dustin Tingley. 51-97 [doi]
- Generating Political Event Data in Near Real Time: Opportunities and ChallengesJohn Beieler, Patrick T. Brandt, Andrew Halterman, Philip A. Schrodt, Erin M. Simpson. 98-120 [doi]
- Network Structure and Social Outcomes: Network Analysis for Social ScienceBetsy Sinclair. 121-139 [doi]
- Ideological Salience in Multiple DimensionsPeter Foley. 140-167 [doi]
- Random Forests and Fuzzy Forests in Biomedical ResearchDaniel Conn, Christina M. Ramirez. 168-196 [doi]
- Big Data, Social Media, and Protest: Foundations for a Research AgendaJoshua A. Tucker, Jonathan Nagler, Megan Macduffee Metzger, Pablo Barberá, Duncan Penfold-Brown, Richard Bonneau. 199-224 [doi]
- Measuring Representational Style in the House: The Tea Party, Obama, and Legislators' Changing Expressed PrioritiesJustin Grimmer. 225-245 [doi]
- Using Social Marketing and Data Science to Make Government SmarterBrian Griepentrog, Sean Marsh, Sidney Carl Turner, Sarah Evans. 246-265 [doi]
- Using Machine Learning Algorithms to Detect Election FraudInés Levin, Julia Pomares, R. Michael Alvarez. 266-294 [doi]
- Centralized Analysis of Local Data, with Dollars and Lives on the Line: Lessons from the Home Radon ExperiencePhillip N. Price, Andrew Gelman. 295-306 [doi]
- Conclusion - Computational Social Science: Toward a Collaborative FutureHanna M. Wallach. 307-316 [doi]