TY - GEN
T1 - Understanding cross-site linking in online social networks
AU - Chen, Yang
AU - Zhuang, Chenfan
AU - Cao, Qiang
AU - Hui, Pan
N1 - Publisher Copyright:
Copyright 2014 ACM.
PY - 2014/8/24
Y1 - 2014/8/24
N2 - Online social networks (OSNs) have attracted billions of users, and play an important role in people's daily life. A user often has accounts on multiple OSN sites. In this paper, we study the emerging "cross-site linking" function, which is supported by many OSNs. Our study is based on Foursquare, a representative location-based social networking (LBSN) service. We conduct a data-driven analysis by using crawled public profiles of almost all (if not all) Foursquare users. Our analysis has shown that the crosssite linking function is widely adopted by Foursquare users, and the users who have enabled this function are more active than other users. We have also found that users who are more concerned with online privacy have a lower probability to enable the cross-site linking function. Besides analyzing crawled Foursquare user profiles, we further explore cross-site linking between Foursquare and other OSN sites, i.e., Facebook and Twitter. The study on"Foursquare- Facebook" linking indicates that users have a high probability to provide consistent information to different OSNs. Meanwhile, "Foursquare-Twitter" linking is used to demonstrate the usefulness of aggregating user-generated content across multiple OSN sites. We present a gender-based analysis of Twitter, which is made accurate by leveraging crosssite links between Foursquare and Twitter.
AB - Online social networks (OSNs) have attracted billions of users, and play an important role in people's daily life. A user often has accounts on multiple OSN sites. In this paper, we study the emerging "cross-site linking" function, which is supported by many OSNs. Our study is based on Foursquare, a representative location-based social networking (LBSN) service. We conduct a data-driven analysis by using crawled public profiles of almost all (if not all) Foursquare users. Our analysis has shown that the crosssite linking function is widely adopted by Foursquare users, and the users who have enabled this function are more active than other users. We have also found that users who are more concerned with online privacy have a lower probability to enable the cross-site linking function. Besides analyzing crawled Foursquare user profiles, we further explore cross-site linking between Foursquare and other OSN sites, i.e., Facebook and Twitter. The study on"Foursquare- Facebook" linking indicates that users have a high probability to provide consistent information to different OSNs. Meanwhile, "Foursquare-Twitter" linking is used to demonstrate the usefulness of aggregating user-generated content across multiple OSN sites. We present a gender-based analysis of Twitter, which is made accurate by leveraging crosssite links between Foursquare and Twitter.
KW - Cross-site linking
KW - Facebook
KW - Foursquare
KW - Measurement
KW - Online social networks
KW - Twitter
UR - https://www.scopus.com/pages/publications/84921720572
U2 - 10.1145/2659480.2659498
DO - 10.1145/2659480.2659498
M3 - 会议稿件
AN - SCOPUS:84921720572
T3 - Proceedings of the 8th Workshop on Social Network Mining and Analysis, SNAKDD 2014
BT - Proceedings of the 8th Workshop on Social Network Mining and Analysis, SNAKDD 2014
PB - Association for Computing Machinery
T2 - 8th Workshop on Social Network Mining and Analysis, SNAKDD 2014
Y2 - 24 August 2014 through 27 August 2014
ER -