Publication Type
Journal Article
Version
acceptedVersion
Publication Date
7-2014
Abstract
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.
Keywords
Analytics, Big data, Computational social science, Data analytics, Interdisciplinary research, Managerial decision-making, Paradigm shift
Discipline
Computational Engineering | Computer Sciences | Numerical Analysis and Scientific Computing
Research Areas
Information Systems and Management; Social Sciences and Computing Systems
Publication
Decision Support Systems
Volume
63
First Page
67
Last Page
80
ISSN
0167-9236
Identifier
10.1016/j.dss.2013.08.008
Publisher
Elsevier
Citation
CHANG, Ray M.; KAUFFMAN, Robert J.; and KWON, Young Ok.
Understanding the paradigm shift to computational social science in the presence of big data. (2014). Decision Support Systems. 63, 67-80.
Available at: https://ink.library.smu.edu.sg/sis_research/2108
Copyright Owner and License
LARC and Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.dss.2013.08.008