DocumentCode
116544
Title
Alike people, alike interests? A large-scale study on interest similarity in social networks
Author
Xiao Han ; Leye Wang ; Soochang Park ; Cuevas, Andres ; Crespi, Noel
Author_Institution
Telecom SudParis, Inst.-Mines Telecom, Évry, France
fYear
2014
fDate
17-20 Aug. 2014
Firstpage
491
Lastpage
496
Abstract
This paper presents a comprehensive empirical study on the correlations between users´ interest similarity and various social features across three interest domains (i.e., movie, music and TV). This study relies on a large dataset, containing 479, 048 users and 5, 263, 351 user-generated interests, captured from Facebook. We identify the social features from three types of the users´ information - demographic information (e.g., age, gender, location), social relations (i.e., friendship), and users´ interests. The results reveal that the interest similarity follows the homophily principle. Particularly, the results show that two users are more likely to be alike in their interests 1) if they exhibit more similarity in their demographic characteristics (e.g., similar age, same gender, or close to each other geographically), or 2) if they are more intimate in their friendship, or 3) if they present a higher average interest individuality (i.e., a measurement for estimating the personalized characteristics of a user´s interests). The empirical observations could be exploited to infer how two users are alike in their interests according to the social features, which could be further harnessed by various practical applications and services, such as recommendation system and advertisement service.
Keywords
behavioural sciences computing; social networking (online); Facebook; advertisement service; demographic characteristics; demographic information; homophily principle; interest domains; interest similarity; recommendation system; social features; social networks; social relations; user interests; user-generated interests; Cities and towns; Conferences; Europe; Facebook; Motion pictures; TV;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/ASONAM.2014.6921631
Filename
6921631
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