讲座题目：Community influence analysis in social network
讲座时间：07月27日（周二）下午3:00-5:00                                  
讲座地点：雁塔校区财经主楼806学术报告厅
讲座人：方匡南
讲座摘要：
Heterogeneous influence detection across network nodes is an important task in network analysis. This paper proposes a community influence model (CIM) by assuming that the nodes can be classified into different communities (i.e., clusters or subgroups) and the nodes within the same community share the common influence parameters. Employing the quasi-maximum likelihood approach, together with the fused lasso-type penalty, we can not only identify the number of communities, but also estimate the influence parameters, without imposing any specific distribution assumption on the error terms. We further demonstrate the resulting estimators enjoy the oracle properties; namely, they perform as well as if the true underlying network structure were given in advance. The proposed approach is also applicable to identify influence nodes under homogeneous setting. To assess the adequacy of the homogeneous influence, the likelihood-ratio type test and its asymptotic theory are established. The performance of our methods is illustrated via simulation studies and an empirical example on coauthor citations for statistical journals.
主办单位：经济与金融学院