Abstract:

Social computing is defined as computing through social media. It refers to the endeavor to understand complex human interactions in social media like blogs, social networking services, wikis, social bookmarking (folksonomies), and online media sharing through computational means. Research in social computing builds on participatory Web characterized by rich Web applications, user generated contents, user enriched contents, user developed widgets, and collaborative environment of participatory web and citizen journalism. Social media has observed a phenomenal growth in past few years. This work focuses on studying the categories of social media and characteristics that make social media immensely popular. Social computing presents both challenges and opportunities. It is a vibrant and fledgling field with many research challenges including phenomenal growth, dynamism, long tail phenomenon, sparse link structure, lack of ground truth, information quality, and data collection. This thesis focuses on the research in Blogosphere--the network of Web logs. Research towards these challenges is presented in the context of the blogosphere, and motivated by the need for identifying influential bloggers in communities, extracting clusters in blogs, and searching for "familiar strangers" in egocentric networks. Novel solutions such as using the network and content information available at the blogosphere simultaneously, leveraging the invaluable and extremely dynamic collective wisdom of the bloggers, constructing social identity of bloggers based on their group affiliations, and providing an evaluation framework that leverages the power of social media to these problems are presented aiming at understanding individuals, communities and their interactions, paving the way for further research and development.