Social computing

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. It is used in two ways as detailed below.

In the weaker sense of the term, social computing has to do with supporting any sort of social behavior in or through computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. Thus, blogs, email, instant messaging, social network services, wikis, social bookmarking and other instances of what is often called social software illustrate ideas from social computing, but also other kinds of software applications where people interact socially.

In the stronger sense of the term, social computing has to do with supporting “computations” that are carried out by groups of people, an idea that has been popularized in James Surowiecki's book, The Wisdom of Crowds. Examples of social computing in this sense include collaborative filtering, online auctions, prediction markets, reputation systems, computational social choice, tagging, and verification games. The Social Information Processing page focuses on this sense of social computing.

Social computing has become more widely known because of its relationship to a number of recent trends. These include the growing popularity of social software and Web 2.0, increased academic interest in social network analysis, the rise of open source as a viable method of production, and a growing conviction that all of this can have a profound impact on daily life. A February 13, 2006 paper by market research company Forrester Research suggested that:

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Easy connections brought about by cheap devices, modular content, and shared computing resources are having a profound impact on our global economy and social structure. Individuals increasingly take cues from one another rather than from institutional sources like corporations, media outlets, religions, and political bodies. To thrive in an era of Social Computing, companies must abandon top-down management and communication tactics, weave communities into their products and services, use employees and partners as marketers, and become part of a living fabric of brand loyalists.

”

Rationale

Social computing begins with the observation that humans — and human behavior — are profoundly social. From birth humans orient to one another, and as they grow they develop abilities for interacting with one another ranging from expression and gesture to spoken and written language. As a consequence, people are remarkably sensitive to the behavior of those around them, and make countless decisions that are shaped by their social context. Whether it's wrapping up a talk when the audience starts fidgeting, choosing the crowded restaurant over the nearly deserted one, or crossing the street against the light because everyone else is doing so, social information provides a basis for inferences, planning, and coordinating activity.

The premise of social computing is that it is possible to design digital systems that support useful functionality by making socially produced information available to their users. This information may be provided directly, as when systems show the number of users who have rated a review as helpful or not. Or the information may be provided after being filtered and aggregated, as is done when systems recommend a product based on what else people with similar purchase history have purchased. Or the information may be provided indirectly, as is the case with Google's page rank algorithms which orders search results based on the number of pages that (recursively) point to them. In all of these cases, information that is produced by a group of people is used to provide or enhance the functioning of a system. Social computing is concerned with systems of this sort and the mechanisms and principles that underlie them.

Social computing can be defined as follows:

Social Computing" refers to systems that support the gathering, representation, processing, use, and dissemination of information that is distributed across social collectivities such as teams, communities,organizations, and markets. Moreover, the information is not "anonymous" but is significant precisely because it is linked to people, who are in turn linked to other people.

Socially intelligent computing

Socially intelligent computing is a new term that refers to the recent efforts of individuals to understand the ways in which systems of people and computers will prove useful as intermediaries between, and tools used by, people. These systems result in new behaviors that occur as a result of the complex interaction between humans and computers.

Examples

Web 2.0

Main article: Web 2.0

A generation of internet applications was developed implementing aspects of social computing developed in the early 21st century.

Enterprise social software

Main article: Enterprise social software

Of particular interest in the realm of social computing is social software for enterprise. Sometimes referred to as "Enterprise 2.0", a term derived from Web 2.0, this generally refers to the use of social computing in corporate intranets and in other medium- and large-scale business environments.

Electronic negotiation and electronic markets

Main article: Electronic negotiation

Electronic negotiation represents an important and desirable coordination mechanism for electronic markets. Negotiation between agents (software agents as well as humans) allows cooperative and competitive sharing of information to determine a proper price. Recent research and practice has also shown that electronic negotiation is beneficial for the coordination of complex interactions among organizations. Electronic negotiation has recently emerged as a very dynamic, interdisciplinary research area covering aspects from disciplines such as Economics, Information Systems, Computer Science, Communication Theory, Sociology and Psychology.

Collaborative filtering

Main article: Collaborative filtering

Collaborative filtering is the method of making automatic predictions (filtering) about the interests of a user by collecting taste information from many users (collaborating). Recommender systems often use it as a "social approach" in order to obtain music, movie, product, web site etc. recommendations.

See also

• Computer-mediated communication
• Human-based computation
• Human-centered computing
• Social Choice
• Game Theory
• Knowledge networking
• Open Innovation
• Social Information Processing
• Sociology
• Symbiotic intelligence
• Web 2.0
• Social Software Engineering
• Multi-agent system
• Social network

External links

• Social Machines - Computing means connecting - Wade Roush, MIT Technology Review, August 2005
• Microsoft Research - Social Computing Group Home
• IBM Research Social Computing Group
• HP Labs Social Computing Lab
• University of Lincoln Social Computing Research Centre
• iCrossing ebook What is Social Media? - Antony Mayfield, 2007
• cs.umn.edu