Scope - Topics of Interest

Scope - Topics of Interest

Overview

The last decade the Social Web is rapidly becoming an important part of our digital lives with shared information in formats that range from text to rich multimedia. Social web networks help to improve the sense of connectedness with real and/or online communities and can be effective communication tools for corporations and groups. Modeling and mining the vast volume of data dynamically produced and maintained in social web environments is a great challenge in an effort to extract, represent and discover meaningful knowledge. Social web mining is a type of data mining, a set of techniques for analyzing social web data to detect patterns. It combines data mining with social computing with the purpose of developing novel algorithms and tools ranging from text and multimedia content mining to web structure mining and community detection. Social web mining is applied in domains such as user modeling, recommendations, personalization, e-learning, e-recruitment, opinion mining, sentiment analysis, visualization, folksonomies, multimedia searching and so on. These trends raise the need for mining big data comprising heterogeneous, dynamic data trails, as well as the critical need for privacy, security and ethical considerations.

Topics of Interest

Topics of interest include (but are not limited to):

  • Recommendations in social media
  • Social web search
  • Sentiment analysis
  • Trust in social media
  • Opinion mining
  • Behaviour analysis, evolution and modeling
  • Information diffusion
  • Personalization for search and social interaction
  • Web mining algorithms
  • Applications of social network analysis
  • Mobile and location-aware social networks
  • Folksonomies and mining tagging systems (blogs, wikis, etc.)
  • Mining social data for multimedia information retrieval
  • Spam detection
  • Usability aspects of social media
  • Social media analysis and visualization
  • Interactive/exploratory processes for social media mining
  • Social networks and big data mining