Social Multimedia Computing

Social multimedia indicates the multimedia data generated and consumed under social media circumstances. As the hybrid of multimedia and social media, social multimedia enjoys advantages of both direct rich sensory simulation and efficient information access and propagation, thus having great potentials in analysis and utilization. Social multimedia computing, a multidisciplinary research and application field, has been developed to understand social multimedia content and connect the social multimedia content with users by exploiting the various social interactions. Social multimedia computing is very different from traditional and web multimedia computing. In traditional multimedia computing, the analysis focus is the multimedia content, and the goal is content understanding and application, e.g., media content analysis, semantic classification and annotation, structured media authoring. Web multimedia computing is heavily related to the WEB1.0 environment, which is dominated by broadcast media developed by professional designers for passive users. Impacted by the participatory WEB 2.0, social multimedia computing features in two perspectives: (1) Since users actively participate in the data generation as well as consumption processes, it is important to exploit the users' interaction and embed social knowledge into the loop of multimedia content understanding. (2) User is the ultimate target of social multimedia information service. Understanding the customized and personalized demands is critical to most social multimedia computing problems.

Co-sponsored by IEEE TCMC and CCF TCMT, this workshop encourages social multimedia computing solutions on multimedia content understanding and user modeling from the above two perspectives. The list of relevant topics includes, but not limited to:

  • Social-sensed multimedia computing
  • Social multimedia mining and data analysis
  • Social multimedia content understanding and retrieval
  • Social multimedia-based user modeling and personalized application
  • Social big data transport and sharing
  • Social networking and media recommendation


  • Peng Cui, BTsinghua University, China

    Peng Cui is an Assistant Professor in Tsinghua University. He got his PhD degree from Tsinghua University in 2010. His research interests include social-sensed multimedia computing, social dynamics modeling and human behavioral modeling. He has published more than 60 papers in prestigious conferences and journals in data mining and multimedia. His recent research won the KDD 2016 Best Paper Finalist, ICDM 2015 Best Student Paper Award, SIGKDD 2014 Best Paper Finalist, IEEE ICME 2014 Best Paper Award, ACM MM12 Grand Challenge Multimodal Award, and MMM13 Best Paper Award. He is the Area Chair of ICDM 2016, ACM MM 2014-2015, IEEE ICME 2014-2015, ICASSP 2013, Associate Editor of ACM TOMM, Elsevier Journal on Neurocomputing. He was the recipient of ACM China Rising Star Award in 2015.

  • Jitao Sang, Institute of Automation, Chinese Academy of Sciences, China

    Jitao Sang is Associate Professor at National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAISA). His research interests include social media analysis, multimedia retrieval and data mining. So far, he has authored one book, filed three patents, co-authored more than 50 journal and conference papers. He is associate editor in Neurocomputing & KSII TIIS, program chair in PCM 2015 & ICIMCS 2015.