TY - GEN
T1 - Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks
AU - Abbasi, Mohammad Ali
AU - Zafarani, Reza
AU - Tang, Jiliang
AU - Liu, Huan
PY - 2014
Y1 - 2014
N2 - Homophily is the formation of social ties between two individuals due to similar characteristics or interests. Based on homophily, in a social network it is expected to observe a higher degree of homogeneity among connected than disconnected people. Many researchers use this simple yet effective principal to infer users' missing information and interests based on the information provided by their neighbors. In a directed social network, the neighbors can be further divided into followers and followees. In this work, we investigate the homophily effect in a directed network. To explore the homophily effect in a directed network, we study if a user's personal preferences can be inferred from those of users connected to her (followers or followees). We investigate which of followers or followees are more effective in helping to infer users' personal preferences. Our findings can help to raise the awareness of users over their privacy and can help them better manage their privacy.
AB - Homophily is the formation of social ties between two individuals due to similar characteristics or interests. Based on homophily, in a social network it is expected to observe a higher degree of homogeneity among connected than disconnected people. Many researchers use this simple yet effective principal to infer users' missing information and interests based on the information provided by their neighbors. In a directed social network, the neighbors can be further divided into followers and followees. In this work, we investigate the homophily effect in a directed network. To explore the homophily effect in a directed network, we study if a user's personal preferences can be inferred from those of users connected to her (followers or followees). We investigate which of followers or followees are more effective in helping to infer users' personal preferences. Our findings can help to raise the awareness of users over their privacy and can help them better manage their privacy.
KW - homophily
KW - preference prediction
KW - relational learning
KW - social media mining
UR - http://www.scopus.com/inward/record.url?scp=84907391264&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84907391264&partnerID=8YFLogxK
U2 - 10.1145/2631775.2631828
DO - 10.1145/2631775.2631828
M3 - Conference contribution
SN - 9781450329545
T3 - HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
SP - 200
EP - 205
BT - HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
PB - Association for Computing Machinery
T2 - 25th ACM Conference on Hypertext and Social Media, HT 2014
Y2 - 1 September 2014 through 4 September 2014
ER -