  With the recent advances of the Internet of Things, and the increasing
accessibility of ubiquitous computing resources and mobile devices, the
prevalence of rich media contents, and the ensuing social, economic, and
cultural changes, computing technology and applications have evolved quickly
over the past decade. They now go beyond personal computing, facilitating
collaboration and social interactions in general, causing a quick proliferation
of social relationships among IoT entities. The increasing number of these
relationships and their heterogeneous social features have led to computing and
communication bottlenecks that prevent the IoT network from taking advantage of
these relationships to improve the offered services and customize the delivered
content, known as relationship explosion. On the other hand, the quick advances
in artificial intelligence applications in social computing have led to the
emerging of a promising research field known as Artificial Social Intelligence
(ASI) that has the potential to tackle the social relationship explosion
problem. This paper discusses the role of IoT in social relationships detection
and management, the problem of social relationships explosion in IoT and
reviews the proposed solutions using ASI, including social-oriented
machine-learning and deep-learning techniques.
