Sunday, September 13, 2009

Social Computing

Social computing is the crucial next step following the rise of personal computing in the evolutionary computing stakes.

The term Social Computing has many connotations. It has come into prominence over the past few years due to the growth of dozens of hugely successful social networks such as Facebook and more recently Twitter; providing a global way of keeping in touch and exchanging information between friends and acquaintances.

In the process of linking with others, a network of social relationships is established. Social computing is in essence a way of codifying and exploring these relationships between people and agents in social spaces- crowds, communities, cities, markets etc.

Social computing applications focus on web-supported online communities such as social networks, wikis, blogs and virtual worlds, providing feedback on interactive social comment, entertainment, scientific and medical advances and business services. It also supports techniques for collective forecasting and decision-making, utilising the combined power of groups and communities to solve difficult problems such as those associated with major disasters and conflict. In addition it is increasingly applied to help analyse how changing technologies and policies affect political, social and cultural behaviour

A set of techniques and algorithms are now being developed based on network, cognitive and evolutionary theory, which will have major ramifications for the enterprise of the future. For example, business strategies and competitive markets have been increasingly characterised by turbulence, uncertainty and complexity. Consequently there is a need to model such markets and strategies as dynamic, evolutionary processes; that is, as complex adaptive systems.

In addition, data mining and simulation are applied to study social networks. Data mining can uncover patterns such as an organisation’s network structure, properties and relationships between suppliers and customers. Agent based social simulation or understanding social phenomena on the basis of models of autonomous agents has also grown tremendously in recent decades. Researchers use this approach to study a wide range of social and economic issues, including social beliefs and norms, resource allocation, traffic patterns, social cooperation, stock market dynamics and organisational decision-making.

There is as yet no effective widely accepted methods for modelling complex systems, especially those involving human behaviour and social organisations, but collaborative agent-based artificial life is currently the most promising approach.

Using agent-based modelling, an enterprise can construct a virtual competitive market that allows business strategists a way of investigating a range of realistic scenarios. For example agent models can account for interactions between irrational and rational investors in stock market bubbles.

The social network paradigm in turn has created the concept of the Social Fabric, which mediates the interactions of the network’s agents and information flows in much the same way as spacetime mediates particle interactions and exchanges. It therefore allows us to explore the dynamic social and cultural aspects of the world in which we live or in which an organisation exists.

Cultural Algorithms or CAs are one of several approaches to modelling the social fabric and the application of social intelligence to solve problems related to optimisation, based on particle or agent swarming. They are therefore a class of computational model derived from observing the cultural evolution process in nature. Embedding an activity or problem in a social fabric can improve its performance or solution outcome, enabling the system to find a better solution than the original over a number of population iterations.

Many organisations have adopted Web 2.0 tools to stimulate innovation and productivity. They are also beginning to embrace social networks as a way of more effectively marketing services and tracking customer behaviour.
But applying social computing to improve the quality of decision-making, process optimisation and prediction scenarios is not yet on the horizon for most.

In the future social computing will be an integral component of the strategic and operational management of the future enterprise, at the same time transforming the web into a truly collaborative and social platform.

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