dc.contributor.author | Chen, Siming | en_US |
dc.contributor.author | Lin, Lijing | en_US |
dc.contributor.author | Yuan, Xiaoru | en_US |
dc.contributor.editor | Meyer, Miriah and Takahashi, Shigeo and Vilanova, Anna | en_US |
dc.date.accessioned | 2017-06-12T05:21:06Z | |
dc.date.available | 2017-06-12T05:21:06Z | |
dc.date.issued | 2017 | |
dc.identifier.issn | 1467-8659 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.1111/cgf13211 | |
dc.identifier.uri | http://dx.doi.org/10.1111/cgf.13211 | |
dc.description.abstract | With the development of social media (e.g. Twitter, Flickr, Foursquare, Sina Weibo, etc.), a large number of people are now using them and post microblogs, messages and multi-media information. The everyday usage of social media results in big open social media data. The data offer fruitful information and reflect social behaviors of people. There is much visualization and visual analytics research on such data. We collect state-of-the-art research and put it into three main categories: social network, spatial temporal information and text analysis. We further summarize the visual analytics pipeline for the social media, combining the above categories and supporting complex tasks. With these techniques, social media analytics can apply to multiple disciplines. We summarize the applications and public tools to further investigate the challenges and trends. | en_US |
dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
dc.title | Social Media Visual Analytics | en_US |
dc.description.seriesinformation | Computer Graphics Forum | |
dc.description.sectionheaders | ST2 | |
dc.description.volume | 36 | |
dc.description.number | 3 | |
dc.identifier.doi | 10.1111/cgf.13211 | |
dc.identifier.pages | 563-587 | |
dc.description.documenttype | star | |