DocumentCode :
3158256
Title :
Predicting Personality with Social Behavior
Author :
Adali, Sarp ; Golbeck, Jennifer
Author_Institution :
Dept. of Comput. Sci., Rensselaer Polytech. Inst., Troy, NY, USA
fYear :
2012
fDate :
26-29 Aug. 2012
Firstpage :
302
Lastpage :
309
Abstract :
In this paper, we examine to which degree behavioral measures can be used to predict personality. Personality is one factor that dictates people´s propensity to trust and their relationships with others. In previous work, we have shown that personality can be predicted relatively accurately by analyzing social media profiles. We demonstrated this using public data from facebook profiles and text from Twitter streams. As social situations are crucial in the formation of one´s personality, one´s social behavior could be a strong indicator of her personality. Given most users of social media sites typically have a large number of friends and followers, considering only these aspects may not provide an accurate picture of personality. To overcome this problem, we develop a set of measures based on one´s behavior towards her friends and followers. We introduce a number of measures that are based on the intensity and number of social interactions one has with friends along a number of dimensions such as reciprocity and priority. We analyze these features along with a set of features based on the textual analysis of the messages sent by the users. We show that behavioral features are very useful in determining personality and perform as well as textual features.
Keywords :
psychology; social networking (online); text analysis; Facebook profiles; Twitter streams; message textual analysis; people trust propensity; personality prediction; priority dimensions; reciprocity dimensions; social behavior; social interaction intensity; social media profiles; social media sites; social situations; textual features; Delay; Educational institutions; Entropy; Media; Standards; Twitter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-2497-7
Type :
conf
DOI :
10.1109/ASONAM.2012.58
Filename :
6425747
Link To Document :
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