Semantic relatedness (SR) is a form of measurement that quantitatively identifies the
relationship between two words or concepts based on the similarity or closeness of their …

Inferring users' interests from their activities on social networks has been an emerging
research topic in the recent years. Most existing approaches heavily rely on the explicit …

Identifying and extracting user communities is an important step towards understanding
social network dynamics from a macro perspective. For this reason, the work in this paper …

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 …

With the growing popularity of microblogging services such as Twitter in recent years, an
increasing number of users are using these services in their daily lives. The huge volume of …

Recent advances in microblog content summarization has primarily viewed this task in the
context of traditional multi-document summarization techniques where a microblog post or …

The automation process for inferring users' interest groups is a challenge task in social
networks research and it has applications in marketing and recommendation systems …

The abundance of user generated content on social media provides the opportunity to build
models that are able to accurately and effectively extract, mine and predict users' interests …

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 …

User modeling based on the user-generated content of users on social networks such as
Twitter has been studied widely, and has been used to provide personalized …