The growth of online social media represents a fundamental shift in the generation, consumption, and sharing of digital information online. Social media data comes in many forms: from blogs (Blogger, LiveJournal) and micro-blogs (Twitter) to social networking (Facebook, LinkedIn, Google+), wikis, social bookmarking (Delicious), reviews (Yelp), media sharing (Youtube, Flickr), and many others. The information inherent in these online conversations is a veritable gold mine with the ability to influence every aspect of a modern enterprise -- from marketing and brand management to product design and customer support. However, the task of drawing concrete, relevant, trustworthy, and actionable insights from the ever increasing volumes of social data presents a significant challenge to current day information management and business intelligence systems. As a result, there is growing interest and activity in the academic and industrial research communities towards various fundamental questions in this space:
  1. How do we collect, curate, and cleanse massive amounts of social media data?
  2. What new analytic techniques, models, and algorithms are required to deal with the unique characteristics of social media data?
  3. How does one combine information extracted from textual content with the structural information in the "network" (linking, sharing, friending, etc.)?
  4. What kind of platforms and infrastructure components are required to support all of these analytic activities at scale?

New : Notifications sent to authors. Camera ready deadline for the accepted papers : Nov 15th 2012, 23:59 PM (UTC -11) 

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