Title: Modeling Influence with Semantics in Social Networks: a Survey,
Abstract: The discovery of influential entities in all kinds of networks (e.g. social,
digital, or computer) has always been an important field of study. In recent
years, Online Social Networks (OSNs) have been established as a basic means of
communication and often influencers and opinion makers promote politics,
events, brands or products through viral content. In this work, we present a
systematic review across i) online social influence metrics, properties, and
applications and ii) the role of semantic in modeling OSNs information. We end
up with the conclusion that both areas can jointly provide useful insights
towards the qualitative assessment of viral user-generated content, as well as
for modeling the dynamic properties of influential content and its flow
dynamics.