TY - GEN
T1 - It takes two to tango
T2 - 14th SIAM International Conference on Data Mining, SDM 2014
AU - Yin, Peifeng
AU - He, Qi
AU - Liu, Xingjie
AU - Lee, Wang-chien
N1 - Publisher Copyright:
Copyright © SIAM.
PY - 2014
Y1 - 2014
N2 - Understanding social tie development among users is crucial for user engagement in social networking services. In this paper, we analyze the social interactions, both online and offline, of users and investigate the development of their social ties using data trail of "how social ties grow" left in mobile and social networking services. To the best of our knowledge, this is the first research attempt on studying social tie development by considering both online and offline interactions in a heterogeneous yet realistic relationship. In this study, we aim to answer three key questions: 1) is there a correlation between online and offline interactions? 2) how is the social tie developed via heterogeneous interaction channels? 3) would the development of social tie between two users be affected by their common friends? To achieve our goal, we develop a Social-aware Hidden Markov Model (SaHMM) that explicitly takes into account the factor of common friends in measure of the social tic development. Our experiments show that, comparing with results obtained using HMM and other heuristic methods, the social tie development captured by our SaHMM is significantly more consistent to lifetime profiles of users.
AB - Understanding social tie development among users is crucial for user engagement in social networking services. In this paper, we analyze the social interactions, both online and offline, of users and investigate the development of their social ties using data trail of "how social ties grow" left in mobile and social networking services. To the best of our knowledge, this is the first research attempt on studying social tie development by considering both online and offline interactions in a heterogeneous yet realistic relationship. In this study, we aim to answer three key questions: 1) is there a correlation between online and offline interactions? 2) how is the social tie developed via heterogeneous interaction channels? 3) would the development of social tie between two users be affected by their common friends? To achieve our goal, we develop a Social-aware Hidden Markov Model (SaHMM) that explicitly takes into account the factor of common friends in measure of the social tic development. Our experiments show that, comparing with results obtained using HMM and other heuristic methods, the social tie development captured by our SaHMM is significantly more consistent to lifetime profiles of users.
UR - http://www.scopus.com/inward/record.url?scp=84959912572&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959912572&partnerID=8YFLogxK
U2 - 10.1137/1.9781611973440.38
DO - 10.1137/1.9781611973440.38
M3 - Conference contribution
AN - SCOPUS:84959912572
T3 - SIAM International Conference on Data Mining 2014, SDM 2014
SP - 334
EP - 342
BT - SIAM International Conference on Data Mining 2014, SDM 2014
A2 - Zaki, Mohammed J.
A2 - Banerjee, Arindam
A2 - Parthasarathy, Srinivasan
A2 - Ning-Tan, Pang
A2 - Obradovic, Zoran
A2 - Kamath, Chandrika
PB - Society for Industrial and Applied Mathematics Publications
Y2 - 24 April 2014 through 26 April 2014
ER -