  Measuring the closeness of friendships is an important problem that finds
numerous applications in practice. For example, online gaming platforms often
host friendship-enhancing events in which a user (called the source) only
invites his/her friend (called the target) to play together. In this scenario,
the measure of friendship closeness is the backbone for understanding source
invitation and target adoption behaviors, and underpins the recommendation of
promising targets for the sources. However, most existing measures for
friendship closeness only consider the information between the source and
target but ignore the information of groups where they are located, which
renders inferior results. To address this issue, we present new measures for
friendship closeness based on the social identity theory (SIT), which describes
the inclination that a target endorses behaviors of users inside the same
group. The core of SIT is the process that a target assesses groups of users as
them or us. Unfortunately, this process is difficult to be captured due to
perceptual factors. To this end, we seamlessly reify the factors of SIT into
quantitative measures, which consider local and global information of a
target's group. We conduct extensive experiments to evaluate the effectiveness
of our proposal against 8 state-of-the-art methods on 3 online gaming datasets.
In particular, we demonstrate that our solution can outperform the best
competitor on the behavior prediction (resp. online target recommendation) by
up to 23.2% (resp. 34.2%) in the corresponding evaluation metric.
