The discovery of community structure in networks is a problem of considerable interest in recent years. In online social networks, often times, users are simultaneously involved in multiple social media sites, some of which share common social relationships. It is of great interest to uncover a shared community structure across these networks. However, in reality, users typically identify thems...

e-Learning has turned to be a necessity for everyone, as it enables continuous and life-long education. Learners are social by nature. They want to connect to othersand share the same interests. Online communities are important to help and encourage learners to continue education. Learners through social capabilities can share different experiences.Social networks are cornerstone for e-Learning...

In this paper, we report on the initial design and implementation of a project entitled RE@L Research Environments Associated with Learning through Social Networks. Our goal is to examine how future science gateways that rely on immersive virtual environments and Web 2.0 technologies can bridge the gap between research and education. To this end, we strategically apply middleware technologies i...

Social networks are analyzed and mined to find communities, or groupings of interrelated entities. Community mining provides this higher level of structure and offers greater understanding, but networks change over time. Their constituent communities change, and the elements of those communities change over time as well. By performing event analysis, the evolutions of communities are abstracted...

Objectives: Our research seeks to examine the correlation between the presence of physical medicine and rehabilitation journals in social networks and the SJR impact factor. Methods: We carried out a correlation study. For the research, we took into account all physical medicine and rehabilitation journals included in the SCImago Journal Rank. The number of followers on Twitter, Facebook, YouT...

Clustering is a major problem when dealing with organizing and dividing data. There are multiple algorithms proposed to handle this issue in many scientific areas such as classifications, community detection and collaborative filtering. The need for clustering arises in Social Networks where huge data generated daily and different relations are established between users. The ability to find gro...