Web 2.0 is about harnessing the potential of the Internet in a more collaborative and peer-to-peer manner with emphasis on social interaction.

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Identifying and analyzing Influencers in online social networks - Part 1

Social Network Analysis (SNA) relates to mapping, understanding, analyzing and measuring interactions across a network of people. Social networks, both formal as well as informal can foster knowledge sharing among participants. This has interesting implications on enterprises wanting to leverage social networks to draw insights and inferences on user preferences as well as user participation in networks. Using SNA, analysts can explore questions related to social networks such as Who are the members to watch?, What are they saying?, Where do they interact?, Strength of interactions, Emergence of sub-groups? etc. This project will explore Social Network Analysis (SNA) and its implications for knowledge discovery in Informal Networks.
Social networks, both formal as well as informal can foster knowledge sharing among participants. The peer-to-peer exchanges that take place in social networking environments go beyond providing direct value to the user. The environment fosters collaboration among the participants; this can lead to an aggregation of content and ideas within sites or sections of sites. Content generated in social networking environments would include discussion threads, logs of chat room conversations, contents of blogs, and any other content posted by users. This collection of content comes from original sources (creation of the user), referenced sources (material cited and presented by users) and aggregated content (collection of material assembled in a unique manner). As long as the members of the group continue to add content of use to the rest of the group, the positive network externalities would draw new members to the group. The accumulation of the content and ideas within successful social networking environments is an aggregation of the collective intelligence of the user community participating in those sites. The accumulated content can be considered an asset that has value, which can be tapped through the right types of analysis methods. This asset has potential value to both the owner of the site as well as others who may wish to purchase the data. This has interesting implications on enterprises wanting to leverage social networks to draw insights and inferences on user preferences as well as user participation in networks.

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Comments

## The accumulated content can be considered an asset that has value, which can be tapped through the right types of analysis methods ##

Tapping and extracting value off a social community/network has always been the bane. While I agree with the whole post, I doubt if the value of the asset can be tapped by the 'right types of analysis methods' alone. Methinks the value SNA is in its 'relationships' and it stops there. The 'asset' as mentioned in the post above can be converted only with extensive participation, collaboration and contribution.

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