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
- National 973 Program of China [2015CB352503]
- Fundamental Research Funds for Central Universities [2016QNA5014]
- National Science Foundation of China [61502416, 61602306]
- Ministry of Education of China [188170-170160502]
- 100 Talents Program of Zhejiang University
- Microsoft Research Asia
- National Science Foundation [DMS-1557593]
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据