Social Computing

This post is based on my thoughts over the social computing concept based on the write up mentioned by Thomas Erikson on Interaction Design Foundation.
Social Computing

The paper describes about the very principles on which  social and collaborative computing thrive.  The researchers elaborate this by giving examples of systems from Amazon, that use the concepts of Computer-Supported Cooperative Work to keep an edge in business, to systems like ESP Game and Wikipedia which are systems completely designed on these principles.

Humans are by nature social beings. Interacting with their communities, colleagues, loved ones and acquaintances. These interactions grow them as individuals and add to the beauty of their daily routine. Social computing relates to these daily online interactions that we do using the digital systems. Social interactions include interactions with not only the people we know but also with the people we do not know. For e.g. buying and selling of goods using auction sites is one example of social interactions that our done with the users we do not know.  The concept of social computing was put a long time ago in the 1960s. The implementation of the concepts came up in the early 1970s, after over a decade. With the growing interest and the introduction of Web, in the early 1990s the digital systems came to be used more than just for social interaction. They started using computers to analyze social interactions and come up with results that further were fed into the system to process and develop newer functionality for the users. This decade gave rise to algorithms that changed the phase of social computing.The Pagerank algorithm was one good example of an efficient way of finding the write content in the pool of user data. Another good example is where Amazon improvised the feature of product reviews by letting users add content in different fashion and brilliantly managed to find an edge over its competitors.

Purely social computing systems have a set of requirements that need to be fulfilled in order to make them efficient and usable. They are:
1.Computation: Finding a set of algorithms that carry out the desired interactions.

2.Recruiting and Motivating: The system has to make sure users are lured to contribute to the system and are motivated to come back to the system frequently in a span of time.

3.Identity and Sociability: The system should let users have their own identity in the system and make sure that they have enough people to interact with.

4. Directing and Focusing activity: The systems should be able to focus user attention and channelize it.

5. Monitoring and Controlling Quality: As there are good aspects to human nature, there are bad ones two.These systems need to be monitored for frauds. As the system get smarter the human ability to find loopholes moves faster too. These system need to be constantly monitored for preventing such occurrences and to maintain quality.

Having a social computing edge in a digital system will add a lot of value to the existing digital system. It draws a lot of users who are willing to be a part of its ecosystem  and bring about the changes faster and better. They can produce efficient, faster and accurate results by making use of unique human abilities. To give a collective view of the value of the social computing systems in today’s digital era is the exponential creation of content in a short time, the accuracy and authenticity of results improves manifold due to exponential participation and in order to represent a community of value the users put their best effort to create content and last but not the least is the unpredictable usage of unique human abilities carrying out varied tasks that cannot be imagined.

I am a frequent user of one such application called Twitter. Twitter is an application where the users have to express their thoughts, suggestions, opinions about a topic or about any of their daily activities in very few words. This system is build around a daily interaction of users. The algorithms collect the tweets from the topics which have the maximum tweets and put this as part of trending topics. The hash tags collect the relevant information and put it in one place. These and many more such algorithms are used to keep users engaged. Each of the users in the application have an identity on twitter called has twitter handle. I feel systems like these really have the ability to create waves in a short span of time because of their multiplying effect. The systems today need to have the right amount of knowledge to incorporate the CSCW concepts into their systems for their success. This not only improves user engagement but also increases user satisfaction with the product.