A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is
Proceedings of the 3rd international workshop on Search and mining user-generated contents - SMUC '11
Users of social media sites, such as Twitter, rapidly generate large volumes of text content on a daily basis. Visual summaries are needed to understand what groups of people are saying collectively in this unstructured text data. Users will typically discuss a wide variety of topics, where the number of authors talking about a specific topic can quickly grow or diminish over time, and what the collective is saying about the subject can shift as a situation develops. In this paper, we present adoi:10.1145/2065023.2065041 dblp:conf/cikm/ArchambaultGCH11 fatcat:uhld6ie25bfadh77b77ze4hj4e