Mining Online Social Spaces in Support of Policy Decision-Making Presentation Transcript
Mining Online Social Spacesin Support of Policy Decision-Making Dana Rotman, PhD candidate February 3, 2010
What do online social spaces offer us? Ever-growing in popularity, online social spaces capture rich data provided by their users Types of available data: Dimensional data – demographics, location, patterns, personal features Structural data – personal ties, interests, commonalities, ratings, favoring, group-memberships Navigational data – movement (clicks) among topics Content – user-generated content, remixes, content reuse, commentary
What tools can we use? Log analysis Social network analysis tools (Hadoop, NodeXL) NLP Manual extraction and analysis of data
YouTube and the Healthcare reform debateAn example of the YouTube healthcare-reform network representingrating and comments
Clusters in the healthcare reform YouTube network
Twitter #Haiti mentionsMentions and retwitts of the hashtag #Haiti, January 27, 2010 (14 days after the earthquake). Several hubs of discussion emerge.
Content of tweets created multiple hubs of topical mentions and information sharing