NDLI: Predicting personality with social behavior: a comparative study

Content Provider	Springer Nature Link
Author	Adalı, Sibel Golbeck, Jennifer
Copyright Year	2014
Abstract	In this paper, we study the problem of predicting personality with features based on social behavior. While network position and text analysis are often used in personality prediction, the use of social behavior is fairly new. Often studies of social behavior either concentrate on a single behavior or trait, or simply use behavior to predict ties that are then used in analysis of network position. To study this problem, we introduce novel features based on a person’s social actions in general, towards specific individuals in particular. We also compute the variation of these actions among all the social contacts of a person as well as the actions of friends. We show that social behavior alone, without the help of any textual or network position information, provides a good basis for personality prediction. We then provide a unique comparative study that finds the most significant features based on social behavior in predicting personality for three different communication mediums: Twitter, SMS and phone calls. These mediums offer us with social behavior from public and private contexts, containing messaging and voice call type exchanges. We find behaviors that are distinctive and normative among the ones we study. We also illustrate how behavioral features relate to different personality traits. We also show the various similarities and differences between different mediums in terms of social behavior. Note that all behavioral features are based on statistical properties of the number and the time of social actions and do not consider the textual content. As a result, they can be applied in many different settings. Furthermore, our findings show us how behavioral features can be customized to a specific medium and personality trait.
Starting Page	1
Ending Page	20
Page Count	20
File Format	PDF
ISSN	18695450
Journal	Social Network Analysis and Mining
Volume Number	4
Issue Number	1
e-ISSN	18695469
Language	English
Publisher	Springer Vienna
Publisher Date	2014-02-08
Publisher Place	Vienna
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Data Mining and Knowledge Discovery Complex Networks Game Theory, Economics, Social and Behav. Sciences Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law Methodology of the Social Sciences
Content Type	Text
Resource Type	Article
Subject	Information Systems Human-Computer Interaction Communication Computer Science Applications Media Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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