Understanding the paradigm shift to computational social science in the presence of big data
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331

초록

The era of big data has created new opportunities for researchers to achieve high relevance and impact amid changes and transformations in how we study social science phenomena. With the emergence of new data collection technologies, advanced data mining and analytics support, there seems to be fundamental changes that are occurring with the research questions we can ask, and the research methods we can apply. The contexts include social networks and blogs, political discourse, corporate announcements, digital journalism, mobile telephony, home entertainment, online gaming, financial services, online shopping, social advertising, and social commerce. The changing costs of data collection and the new capabilities that researchers have to conduct research that leverages micro-level, meso-level and macro-level data suggest the possibility of a scientific paradigm shift toward computational social science. The new thinking related to empirical regularities analysis, experimental design, and longitudinal empirical research further suggests that these approaches can be tailored for rapid acquisition of big data sets. This will allow business analysts and researchers to achieve frequent, controlled and meaningful observations of real-world phenomena. We discuss how our philosophy of science should be changing in step with the times, and illustrate our perspective with comparisons between earlier and current research inquiry. We argue against the assertion that theory no longer matters and offer some new research directions. (C) 2013 Elsevier B.V. All rights reserved.

키워드

AnalyticsBig dataComputational social scienceData analyticsInterdisciplinary researchManagerial decision-makingParadigm shiftPRICE DISPERSIONONLINEINFORMATIONBUSINESSBEHAVIORDESIGNTRANSPARENCYANALYTICSAUCTIONSMARKETS
제목
Understanding the paradigm shift to computational social science in the presence of big data
저자
Chang, Ray M.Kauffman, Robert J.Kwon, YoungOk
DOI
10.1016/j.dss.2013.08.008
발행일
2014-07
유형
Article
저널명
Decision Support Systems
63
페이지
67 ~ 80