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Special Issue on Social Media Analytics and Learning

posted Sep 5, 2013, 6:48 AM by Christian Timmerer

Elsevier Neurocomputing Journal Special Issue on 

Social Media Analytics and Learning

http://www.journals.elsevier.com/neurocomputing/call-for-papers/special-issue-on-social-media-analytics-and-learning/

Aim and Scope:

Online social platforms have developed to a virtual world where users record, share/broadcast, and comment on various snapshots of their real lives and various facets of the real world, leading to an explosive proliferation of social media on the Internet. For example, Flickr and YouTube offer places for media sharing among users; and Facebook, Twitter, and Instagram enable users to connect with their social audiences through media content (e.g., images/videos). The availability of massive and heterogeneous social media data, consisting of media content, users, social context, geo-locations, and other metadata, have created numerous new research opportunities and challenges. Consequently, social media analytic and learning has become an increasingly attractive research direction. More and more research efforts have been dedicated to key issues therein, such as analytics and learning techniques towards understanding social media, social media analytics tools and systems, knowledge mining from social media, as well as social network modeling, etc.

This special issue seeks contributions reporting novel solutions, models, theories, or systems regarding social media analytics and learning. Topics of interest include but not limited to:

  • Understanding social content and dynamics
  • Efficient learning algorithms for scalable social media analytics
  • Social network modeling
  • Machine learning and data mining for social media
  • User interests and behavior modeling in social media
  • Tagging, semantic annotation, object and event recognition on large-scale social media collections
  • Indexing, ranking, and retrieval on large-scale social media collections
  • Benchmark dataset construction for analytics and learning on social media
  • Open-source software libraries for analytics and learning on social media

Important Dates:

  • Paper Submission: November 01, 2013
  • First Notification: January 01, 2014
  • Revised Manuscript: March 15, 2014
  • Notification of Acceptance: May 15, 2014
  • Final Manuscript: June 07, 2014             

Guest Editors:

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