Journal
PROCEEDINGS OF THE IEEE
Volume 102, Issue 12, Pages 1934-1939Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JPROC.2014.2359054
Keywords
Big data; personality; psychology; social networks
Categories
Funding
- F.R.S.-Fonds de la Recherche Scientifique (FNRS)
- European Union (EU) project Optimizr
- COST Action [TD1210 KnowEscape]
- Psychometrics Centre at the University of Cambridge
- Boeing Corporation
- Microsoft Research
- National Science Foundation (NSF)
- Defense Advanced Research Projects Agency (DARPA)
- Center for the Study of Language and Information at Stanford University (CLSI)
- Interuniversity Attraction Poles Programme
- Belgian State, Science Policy Office
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A growing portion of offline and online human activities leave digital footprints in electronic databases. Resulting big social data offers unprecedented insights into population-wide patterns and detailed characteristics of the individuals. The goal of this paper is to review the literature showing how pervasive records of digital footprints, such as Facebook profile, or mobile device logs, can be used to infer personality, a major psychological framework describing differences in individual behavior. We briefly introduce personality and present a range of works focusing on predicting it from digital footprints and conclude with a discussion of the implications of these results in terms of privacy, data ownership, and opportunities for future research in computational social science.
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