TY - GEN
T1 - From the periphery to the center
T2 - 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
AU - Yan, Bo
AU - Liu, Yiping
AU - Liu, Jiamou
AU - Cai, Yijin
AU - Su, Hongyi
AU - Zheng, Hong
N1 - Publisher Copyright:
© 2018 International Joint Conferences on Artificial Intelligence. All right reserved.
PY - 2018
Y1 - 2018
N2 - Interpersonal ties are pivotal to individual efficacy, status and performance in an agent society. This paper explores three important and interrelated themes in social network theory: the center/periphery partition of the network; network dynamics; and social integration of newcomers. We tackle the question: How would a newcomer harness information brokerage to integrate into a dynamic network going from periphery to center? We model integration as the interplay between the newcomer and the dynamics network and capture information brokerage using a process of relationship building. We analyze theoretical guarantees for the newcomer to reach the center through tactics; proving that a winning tactic always exists for certain types of network dynamics. We then propose three tactics and show their superior performance over alternative methods on four real-world datasets and four network models. In general, our tactics place the newcomer to the center by adding very few new edges on dynamic networks with ≈ 14000 nodes.
AB - Interpersonal ties are pivotal to individual efficacy, status and performance in an agent society. This paper explores three important and interrelated themes in social network theory: the center/periphery partition of the network; network dynamics; and social integration of newcomers. We tackle the question: How would a newcomer harness information brokerage to integrate into a dynamic network going from periphery to center? We model integration as the interplay between the newcomer and the dynamics network and capture information brokerage using a process of relationship building. We analyze theoretical guarantees for the newcomer to reach the center through tactics; proving that a winning tactic always exists for certain types of network dynamics. We then propose three tactics and show their superior performance over alternative methods on four real-world datasets and four network models. In general, our tactics place the newcomer to the center by adding very few new edges on dynamic networks with ≈ 14000 nodes.
UR - http://www.scopus.com/inward/record.url?scp=85055682476&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85055682476
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 3912
EP - 3918
BT - Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
A2 - Lang, Jerome
PB - International Joint Conferences on Artificial Intelligence
Y2 - 13 July 2018 through 19 July 2018
ER -