The project SOCWEB (Searching the social Web) aimed to determine how knowledge and insights available through user-generated content on SNs can be used to improve users' Web search experiences. Research focused on SN data management (how to efficiently monitor, download and manage social Web data); socially aware results (taking into account a user's SN during information searches); social searches (enabling users to save and share their Web searches with other users); and social trust (how to determine which user is trustworthy and knowledgeable on a given topic). Work in the first phase accomplished goals related to SN data management and the ability of users to benefit from their SNs when searching the Web. The team developed a platform that mines data generated from multiple SNs such as Facebook and Twitter. This crawler retrieves pages from the Web on a given topic and then assesses the content of each page to determine if it is relevant to the topic. SOCWEB also created algorithms to identify content users may be interested in but don't know about. Project efforts and outcomes have been presented in several publications in top journals and at conferences. Additionally, some of the work contributed to Masters of Science theses – one titled 'Topic-Sensitive Hidden-Web Crawling' and the other titled 'Efficient Monitoring of Network Activities'. It also supported completion of a PhD dissertation titled 'Data Mining Techniques on Web Personalization'. More information on publications, results and data collected so far is available on the project website. The site also has a live demo of the system developed for supporting social searches on the Web. SOCWEB delivered new and improved techniques for discovering, retrieving, ranking and managing content in the social Web. The results of this initiative will help provide users with more useful information during their Web information searches.
Social networking, Web searches, social networks, social web, user-generated content, data management