Details

Autor(en) / Beteiligte

• Yingcai Wu
• Nan Cao
• Gotz, David
• Yap-Peng Tan
• Keim, Daniel A.

Titel

A Survey on Visual Analytics of Social Media Data

Ist Teil von

• IEEE transactions on multimedia, 2016-11, Vol.18 (11), p.2135-2148

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2016

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• 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.