Frontiers of Engineering Reports on Leading-Edge Engineering from the 2013 Symposium (2014) / Chapter Skim
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Computational Social Science: Exciting Progress and Future Directions--Duncan J. Watts
Computational Social Science: Exciting Progress and Future Directions--Duncan J. Watts
Pages 17-24
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From page 17... ...
Over the same period, and driven by the same explosion in data, the study of social phenomena has increasingly become the province of computer scientists, physicists, and other "hard" scientists. Papers on social networks and related topics appear routinely in top science journals and computer science conferences; network science research centers and institutes are sprouting up at top universities; and funding agencies from DARPA to NSF have moved quickly to embrace what is being called computational social science.
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From page 18... ...
the complexity of the theoretical issues confronting social science, (2) the difficulty of obtaining the rel
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From page 19... ...
. The most prominent strand of research in computational social science leverages communication technologies -- including email, social networking and microblogging services, and cellphones -- as well as online games, ecommerce sites, and other Internet-enabled services.
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From page 20... ...
Challenges and Opportunities for Computational Social Science As impressive as its recent accomplishments have been, computational social science faces a number of pressing challenges if it is to address the important questions of social science in a meaningful way. For example, organizational and interorganizational problem solving, collective action and decision making, the relationship between deliberation, governance, and democracy, the emergence of disruptive technologies, and the rise of new political or cultural movements are all core social scientific questions, but they have received little attention from computational social science largely on the grounds of limits to current data sources, platforms, or methods.
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From page 21... ...
Expanding Virtual Labs A second challenge for computational social science concerns the continued development of experimental macrosociology. Perhaps surprisingly, the major limitation to existing experimental designs is not technical but rather logistical -- namely, the difficulty of recruiting large numbers of subjects in a reliable and cost-effective manner.
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From page 22... ...
My view, however, is that meaningful progress on important problems will require serious engagement between the communities, each of which has much to offer the other: computer scientists have technical capabilities that are of great potential benefit to social scientists, and the latter's deep subject matter knowledge is essential in order to ask the right questions and to formulate even simple models in ways that address these questions. New Institutions for Computational Social Science Unfortunately, harnessing the complementary strengths of multiple research communities is easier said than done.
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From page 23... ...
As exciting and important as this development is, however, social science is not and should not become a subfield of computer science or "data science." Just as in computational biology, the computational element of computational social science should remain in service to the substantive and substantial questions of social science. Achieving this goal will require significant investments in new sources of data, new platforms for organizing existing data, and new institutional arrangements for fostering team-based interdisciplinary research.
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From page 24... ...
2009. Computational social science.
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