Social Network Computing

Introduction

Social computing is a general term for an area of computer science that is concerned with the intersection of social behavior and computational systems. It has become an important concept for use in business. Example of social computing in this sense include collaborative filtering, online auctions, prediction markets, reputation systems, computational social choice, and verification games.


Research Area

  1. Social Network Analysis
    Social Network Analysis (SNA) refers to methods used to analyze social network, social structures made up of individuals (or organizations) called "nodes", which are tied (connected) by one or more specific types of interdependency, such as friendship, kinship, common interest, financial exchange, or relationships of beliefs. We also analyze social network structure and its data and study on discovery of communities on social network.



  2. Community Detection
    In complex social networks, a networks is said to have community structure if the nodes of the network can be easily grouped into sets of nodes such that each set of nodes is densely connected internally. This is an important technique to find out communities on multipartite network, directed and weighted network. Because a node of social network can belong to several communities, this research area is focused on specific method to detect overlapping community.



  3. Human Computer Interaction on Social Network
    Social network analysis(SNA) Is the systematic study of collections of social relationships, which consist of social actors implicitly or explicitly connected to one another. Human computer interaction(HCI) seeks to improve the ways people interact with information systems, many of which support interactions between people. SNA can be applied in many ways to HCI concerns, providing theory and method for better understanding and evaluating the diffusion and impact of Computer supported cooperative work innovations like social media systems.