Welcome

The field of social computing has two different foci: social and computational. There is the focus on socialness of social software or social web applications. Widespread examples of social software are blogs, wikis, social bookmarking services, instant messaging services, and social networking sites. Social computing often uses various types of crowdsourcing techniques for aggregation of input from numerous users (public at large). Tools such as prediction markets, social tagging, reputation and trust systems as well as recommender systems are based on collaborative filtering and thus a result of crowdsourcing.

Another focus of social computing is on computational modeling of social behavior, among others through Multi-agent systems (MAS) and Social Networks (SN). MAS have an anchoring going beyond social sciences even when a sociological terminology is often used. There are several usages of MAS: to design distributed and/or hybrid systems; to develop philosophical theory; to understand concrete social facts, or to answer concrete social issues via modelling and simulation. MAS aim at modelling, among other things, cognitive or reactive agents who interact in dynamic environments where they possibly depend on each other to achieve their goals. The emphasis is nowadays on constructing complex computational systems composed by agents which are regulated by various types of norms, and behave like human social systems.

Finally, Social networks (SN) are social structures made of nodes (which are, generally, individuals or organizations) that are tied by one or more specific types of interdependency, such as values, visions, idea, financial exchange, friends, kinship, dislike, conflict, trade, web links, disease transmission, among many others. Social networks analysis plays a critical role in determining the way specific problems are solved, organizations are run, and the degree to which individuals succeed in achieving their goals. Social networks analysis has addressed also the dynamics issue, called dynamic networks analysis. This is an emergent scientific field that brings together traditional social network analysis, link analysis and multi-agent systems.


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