Over the years, the recommender systems (RS) have witnessed an increasing growth for its
enormous benefits in supporting users' needs through mapping the available products to …

Online social networks have become a fundamental part of the global online experience.
They facilitate different modes of communication and social interactions, enabling …

Social network users publicly share a wide variety of information with their followers and the
general public ranging from their opinions, sentiments and personal life activities. There has …

The accurate prediction of users' future interests on social networks allows one to perform
future planning by studying how users will react if certain topics emerge in the future. It can …

Social networks enable users to freely communicate with each other and share their recent
news, ongoing activities or views about different topics. As a result, they can be seen as a …

Researchers have developed various approaches for exploring the spatial information,
temporal patterns, and Twitter content in topics of interest in order to generate a better …

This paper introduces ComModeler, a novel approach for topic modeling using community
finding in dynamic networks. Our algorithm first extracts the terms/keywords, formulates a …

User communities in social networks are usually identified by considering explicit structural
social connections between users. While such communities can reveal important information …

In this paper, we analyze a dataset including more than 189 million tweets related to the first
month of the 2022 war in Ukraine. Our analysis especially focuses on communities of Twitter …

The large scale and complex structure of real networks bring enormous challenges to
traditional community detection methods. In order to detect community structure in large …