TY - GEN
T1 - Maximizing acceptance probability for active friending in online social networks
AU - Yang, De Nian
AU - Hung, Hui Ju
AU - Lee, Wang Chien
AU - Chen, Wei
N1 - Publisher Copyright:
Copyright © 2013 ACM.
PY - 2013/8/11
Y1 - 2013/8/11
N2 - Friending recommendation has successfully contributed to the explosive growth of online social networks. Most friending recommendation services today aim to support passive friending, where a user passively selects friending targets from the recommended candidates. In this paper, we advocate a recommendation support for active friending, where a user actively specifies a friending target. To the best of our knowledge, a recommendation designed to provide guidance for a user to systematically approach his friending target has not been explored for existing online social networking services. To maximize the probability that the friending target would accept an invitation from the user, we formulate a new optimization problem, namely, Acceptance Probability Maxi- mization (APM), and develop a polynomial time algorithm, called Selective Invitation with Tree and In-Node Aggrega-Tion (SITINA), to find the optimal solution. We implement an active friending service with SITINA on Facebook to validate our idea. Our user study and experimental results reveal that SITINA outperforms manual selection and the baseline approach in solution quality efficiently.
AB - Friending recommendation has successfully contributed to the explosive growth of online social networks. Most friending recommendation services today aim to support passive friending, where a user passively selects friending targets from the recommended candidates. In this paper, we advocate a recommendation support for active friending, where a user actively specifies a friending target. To the best of our knowledge, a recommendation designed to provide guidance for a user to systematically approach his friending target has not been explored for existing online social networking services. To maximize the probability that the friending target would accept an invitation from the user, we formulate a new optimization problem, namely, Acceptance Probability Maxi- mization (APM), and develop a polynomial time algorithm, called Selective Invitation with Tree and In-Node Aggrega-Tion (SITINA), to find the optimal solution. We implement an active friending service with SITINA on Facebook to validate our idea. Our user study and experimental results reveal that SITINA outperforms manual selection and the baseline approach in solution quality efficiently.
UR - http://www.scopus.com/inward/record.url?scp=84962053885&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962053885&partnerID=8YFLogxK
U2 - 10.1145/2487575.2487599
DO - 10.1145/2487575.2487599
M3 - Conference contribution
AN - SCOPUS:84962053885
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 713
EP - 721
BT - KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
A2 - Parekh, Rajesh
A2 - He, Jingrui
A2 - Inderjit, Dhillon S.
A2 - Bradley, Paul
A2 - Koren, Yehuda
A2 - Ghani, Rayid
A2 - Senator, Ted E.
A2 - Grossman, Robert L.
A2 - Uthurusamy, Ramasamy
PB - Association for Computing Machinery
T2 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013
Y2 - 11 August 2013 through 14 August 2013
ER -