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DESCRIPTION:Click for Latest Location Information: http://smartdata2015.dataversity.net/sessionPop.cfm?confid=91&proposalid=7773\nThis presentation will show what we’ve learned taking on huge collections of user generated content (“UGC”), with the aim of discovering actionable insights by applying text-mining and semantic analysis. For over a year, we’ve analyzed the entire data set of DISQUS (by far the largest third-party commenting platform, with over 70% market-share and over 300 million active users). \nSpecifically we will explain and illustrate, by our own case-studies, each of the following “lessons\nlearned”:  \nWhen there is no “wisdom of the crowds,” wisdom can be gleaned from data about the crowds\nThe self-selecting nature of UGC is a blessing or a curse depending on how refined your filters are\nIn evaluative commenting, what users say is their bottom-line, often isn’t\nIn forward-looking comments, what users wish would happen can be a better predictor than their actual predictions\nIt’s a myth that user commentary on articles is either just band-wagon or flame-war; many comments add relevant breadth and depth, and there is a way to harness that\nBesides showing a concrete example of each of the above, we’ll give tips on how to effectively manage the massive data set and the fact that it changes around the clock.  We will focus on how to uncover insights that are valuable to a variety of stakeholders including marketers, merchandisers, and publishers.  We’ll clearly outline the components that anyone needs for “distilling the essence” of massive user generated content.
DTSTART:20150819T150000
SUMMARY:Being Smart About Aggregated User Content:  Lessons Learned from Analyzing One of the Largest Repositories of User Generated Content Ever Assembled
DTEND:20150819T154459
LOCATION: See Description
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