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Social Network Fusion and Mining: A Survey
Looking from a global perspective, the landscape of online social networks is
highly fragmented. A large number of online social networks have appeared,
which can provide users with various types of services. Generally, the
information available in these online social networks is of diverse categories,
which can be represented as heterogeneous social networks (HSN) formally.
Meanwhile, in such an age of online social media, users usually participate in
multiple online social networks simultaneously to enjoy more social networks
services, who can act as bridges connecting different networks together. So
multiple HSNs not only represent information in single network, but also fuse
information from multiple networks.
Formally, the online social networks sharing common users are named as the
aligned social networks, and these shared users who act like anchors aligning
the networks are called the anchor users. The heterogeneous information
generated by users' social activities in the multiple aligned social networks
provides social network practitioners and researchers with the opportunities to
study individual user's social behaviors across multiple social platforms
simultaneously. This paper presents a comprehensive survey about the latest
research works on multiple aligned HSNs studies based on the broad learning
setting, which covers 5 major research tasks, i.e., network alignment, link
prediction, community detection, information diffusion and network embedding
respectively.Comment: 64 page