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A view from data science

delete2021-09-15
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OA
AI
A
Anna Sapienza *
S
Sune Lehmann
DOI:10.1177/20539517211040198delete
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Abstract

Abstract

En 中文
For better and worse, our world has been transformed by Big Data. To understand digital traces generated by individuals, we need to design multidisciplinary approaches that combine social and data science. Data and social scientists face the challenge of effectively building upon each other's approaches to overcome the limitations inherent in each side. Here, we offer a data science perspective on the challenges that arise when working to establish this interdisciplinary environment. We discuss how we perceive the differences and commonalities of the questions we ask to understand digital behaviors (including how we answer them), and how our methods may complement each other. Finally, we describe what a path toward common ground between these fields looks like when viewed from data science.
Keywords:
Interdisciplinary approach
social data science
digital behavior

Journal

Big Data and Society cover
Big Data and Society
IF:
5.9
Papers:
718
Citations:
5.3K

Organization

U
University of Copenhagen
Scholars:
7.6W
Papers: 6.6W
Citations: 86
T
technical university of denmark
Scholars:
2.6W
Papers: 2.8W
Citations: 37
Cited Papers

Cited Papers

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Interdisciplinary research has consistently lower funding success
errNATURE
IF48.5
err2016-06-29
err368
PREAI
errBromham, Lindell; Dinnage, Russell; Hua, Xia
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SOCIAL SCIENCE Computational Social Science
errSCIENCE
IF45.8
err2009-02-06
err2.3K
errOAAI
errLazer, David; Pentland, Alex; Adamic, Lada; Aral, Sinan; Barabasi, Albert-Laszlo; Brewer, Devon; Christakis, Nicholas; Contractor, Noshir; Fowler, James; Gutmann, Myron; Jebara, Tony; King, Gary; Macy, Michael; Roy, Deb; Van Alstyne, Marshall
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