TY - GEN
T1 - An Empirical Study on Preference Distribution of Facebook Users
AU - Wang, Leye
AU - Han, Xiao
AU - Chen, Longbiao
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/12
Y1 - 2017/1/12
N2 - Online social networks connect users all around the world, now is becoming a valuable crowdsourced data source for implementing intelligent people-centric services, e.g., personalized recommendations. Understanding users' characteristics, behaviors is critical for enabling such intelligent services. This paper studies users' preference distribution based on a huge Facebook dataset with 479,048 users, 11 preference types, 879,868 distinct preference items, 6,276,422 preference items. We observe that Music, TV, Movie are the most popular preference types on Facebook, users share more common items in TV, Movie, Sport, Music than the other preference types. We also find that the preference popularity distribution follows power law. In addition, we investigate the effects of users' location on the distribution of the popular preferences, conclude that the most popular preferences are very different among different countries. For instance, only one same Music ('Michael Jackson'), one same TV ('Family Guy'), no same Movie present as the top 10 preference items in all of US, Denmark, Germany.
AB - Online social networks connect users all around the world, now is becoming a valuable crowdsourced data source for implementing intelligent people-centric services, e.g., personalized recommendations. Understanding users' characteristics, behaviors is critical for enabling such intelligent services. This paper studies users' preference distribution based on a huge Facebook dataset with 479,048 users, 11 preference types, 879,868 distinct preference items, 6,276,422 preference items. We observe that Music, TV, Movie are the most popular preference types on Facebook, users share more common items in TV, Movie, Sport, Music than the other preference types. We also find that the preference popularity distribution follows power law. In addition, we investigate the effects of users' location on the distribution of the popular preferences, conclude that the most popular preferences are very different among different countries. For instance, only one same Music ('Michael Jackson'), one same TV ('Family Guy'), no same Movie present as the top 10 preference items in all of US, Denmark, Germany.
UR - https://www.scopus.com/pages/publications/85013197039
U2 - 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0167
DO - 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0167
M3 - 会议稿件
AN - SCOPUS:85013197039
T3 - Proceedings - 13th IEEE International Conference on Ubiquitous Intelligence and Computing, 13th IEEE International Conference on Advanced and Trusted Computing, 16th IEEE International Conference on Scalable Computing and Communications, IEEE International Conference on Cloud and Big Data Computing, IEEE International Conference on Internet of People and IEEE Smart World Congress and Workshops, UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld 2016
SP - 1069
EP - 1073
BT - Proceedings - 13th IEEE International Conference on Ubiquitous Intelligence and Computing, 13th IEEE International Conference on Advanced and Trusted Computing, 16th IEEE International Conference on Scalable Computing and Communications, IEEE International Conference on Cloud and Big Data Computing, IEEE International Conference on Internet of People and IEEE Smart World Congress and Workshops, UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld 2016
A2 - El Baz, Didier
A2 - Bourgeois, Julien
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Conference on Ubiquitous Intelligence and Computing, 13th IEEE International Conference on Advanced and Trusted Computing, 16th IEEE International Conference on Scalable Computing and Communications, IEEE International Conference on Cloud and Big Data Computing, IEEE International Conference on Internet of People and IEEE Smart World Congress and Workshops, UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld 2016
Y2 - 18 July 2016 through 21 July 2016
ER -