Social interactions, such as eye contact, speaking and listening, are ubiquitous in our life
and carry important clues of human's social status and psychological state. With evolving …

Network embedding fills the gap of applying tuple-based data mining models to networked
datasets through learning latent representations or embeddings. However, it may not be …

Modern sociology has profoundly uncovered many convincing social criteria for behavioral
analysis. Unfortunately, many of them are too subjective to be measured and very …

In location-based social networks (LBSNs), users implicitly interact with each other by
visiting places, issuing comments and/or uploading photos. These heterogeneous …

Self-identity in mobile location-based social networks (LBSN) is a relatively underexplored
topic. In this paper, we present our initial understandings on the role that LBSN play in the …

Inferring social relationships from user location data has become increasingly important for
real-world applications, such as recommendation, advertisement targeting, and …

Generating friend recommendations in location-based social networks is a challenging task,
as we have to learn how different contextual factors influence users' behavior to form social …

Location plays an essential role in our lives, bridging our online and offline worlds. This
paper explores the interplay of people's location, interactions, and social ties within a large …

Location-based social networks (LBSNs) have become a popular form of social media in
recent years. They provide location related services that allow users to" check-in''at …

Popularity of Location-based Social Networks (LBSNs) provides an opportunity to collect
massive multi-modal datasets that contain geographical information, as well as time and …