4.7 Article

A Survey on Visual Analytics of Social Media Data

期刊

IEEE TRANSACTIONS ON MULTIMEDIA
卷 18, 期 11, 页码 2135-2148

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMM.2016.2614220

关键词

Social media data; visual analytics; visualization

资金

  1. National 973 Program of China [2015CB352503]
  2. Fundamental Research Funds for Central Universities [2016QNA5014]
  3. National Science Foundation of China [61502416, 61602306]
  4. Ministry of Education of China [188170-170160502]
  5. 100 Talents Program of Zhejiang University
  6. Microsoft Research Asia
  7. National Science Foundation [DMS-1557593]

向作者/读者索取更多资源

The unprecedented availability of social media data offers substantial opportunities for data owners, system operators, solution providers, and end users to explore and understand social dynamics. However, the exponential growth in the volume, velocity, and variability of social media data prevents people from fully utilizing such data. Visual analytics, which is an emerging research direction, has received considerable attention in recent years. Many visual analytics methods have been proposed across disciplines to understand large-scale structured and unstructured social media data. This objective, however, also poses significant challenges for researchers to obtain a comprehensive picture of the area, understand research challenges, and develop new techniques. In this paper, we present a comprehensive survey to characterize this fast-growing area and summarize the state-of-the-art techniques for analyzing social media data. In particular, we classify existing techniques into two categories: gathering information and understanding user behaviors. We aim to provide a clear overview of the research area through the established taxonomy. We then explore the design space and identify the research trends. Finally, we discuss challenges and open questions for future studies.

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