TY - GEN
T1 - Alike people, alike interests? A large-scale study on interest similarity in social networks
AU - Han, Xiao
AU - Wang, Leye
AU - Park, Soochang
AU - Cuevas, Ángel
AU - Crespi, Noël
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/10
Y1 - 2014/10/10
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/84911013848
U2 - 10.1109/ASONAM.2014.6921631
DO - 10.1109/ASONAM.2014.6921631
M3 - 会议稿件
AN - SCOPUS:84911013848
T3 - ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
SP - 491
EP - 496
BT - ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
A2 - Wu, Xindong
A2 - Wu, Xindong
A2 - Ester, Martin
A2 - Xu, Guandong
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014
Y2 - 17 August 2014 through 20 August 2014
ER -