SOCIAL INFORMATION PROCESSING AND DISTRIBUTED COMPUTING

One of the challenges in the analysis of big data is the ability to process data with large velocity, volume, and variety quickly and effectively. We believe the future of analytics will enable this more effectively through two networking concepts, social information processing (SIP) and distributed computing. SIP is the idea that “computation” or analysis is carried out by groups of people. It is “an activity through which collective human actions organize knowledge.”4 It is the creation and processing of information by a group of people. Simple examples of SIP include collaborative filtering, online auctions, prediction markets, online reputation systems, and verification games. We think SIP will play a significant role in the future of analytics in several ways. One simple example is that analysts’ social networks will evolve whereby they collectively share and improve algorithms and analytical techniques. Another way is that users of data themselves may create and share their own analytical models with one another, using analytical tools, thereby creating meta models that describe and predict the data patterns for the system. For example, in the future, users may use body tracking technology to record data on their activities, food intake, exercise, and health vital signs over long periods of time. The tracking technology may include a customized algorithm that allows the user to predict which factors (type of exercise, ...

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