Detecting a community in a network is a matter of discerning the distinct features and
connections of a group of members that are different from those in other communities. The …

With the rapid development of information technologies, various big graphs are prevalent in
many real applications (eg, social media and knowledge bases). An important component of …

To meet the requirement of social influence analytics in various applications, the problem of
influence maximization has been studied in recent years. The aim is to find a limited number …

Influence maximization has recently received significant attention for scheduling online
campaigns or advertisements on social network platforms. However, most studies only focus …

Depression has become a big problem in our society today. It is also a major reason for
suicide, especially among teenagers. In the current outbreak of coronavirus disease (COVID …

The popularity of various social media platforms (eg, Twitter, Facebook, Instagram, and
Weibo) has led to the generation of millions of micro-blogs each day. Retweet (message …

Community search enables personalized community discovery and has wide applications in
large real-world graphs. While community search has been extensively studied for …

The problem of k-truss search has been well defined and investigated to find the highly
correlated user groups in social networks. But there is no previous study to consider the …

Distance labeling approaches are widely adopted to speed up the online performance of
shortest distance queries. The construction of the distance labeling, however, can be …

Shortest path computation is a fundamental operation in small-world networks and index-
based methods, especially 2-hop labeling, are commonly applied which have achieved high …