Envisioning information
Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
ThemeRiver: Visualizing Thematic Changes in Large Document Collections
IEEE Transactions on Visualization and Computer Graphics
Cluster merging and splitting in hierarchical clustering algorithms
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Visualizing the non-visual: spatial analysis and interaction with information from text documents
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
Tree-Maps: a space-filling approach to the visualization of hierarchical information structures
VIS '91 Proceedings of the 2nd conference on Visualization '91
Turning the Bucket of Text into a Pipe
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
Getting our head in the clouds: toward evaluation studies of tagclouds
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ACM Transactions on the Web (TWEB)
Combining DagMaps and Sugiyama Layout for the Navigation of Hierarchical Data
IV '07 Proceedings of the 11th International Conference Information Visualization
Scented Widgets: Improving Navigation Cues with Embedded Visualizations
IEEE Transactions on Visualization and Computer Graphics
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Effectiveness of Animation in Trend Visualization
IEEE Transactions on Visualization and Computer Graphics
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Tweet the debates: understanding community annotation of uncollected sources
WSM '09 Proceedings of the first SIGMM workshop on Social media
Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines
IEEE Transactions on Visualization and Computer Graphics
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Recommending twitter users to follow using content and collaborative filtering approaches
Proceedings of the fourth ACM conference on Recommender systems
A Visual Backchannel for Large-Scale Events
IEEE Transactions on Visualization and Computer Graphics
SparkClouds: Visualizing Trends in Tag Clouds
IEEE Transactions on Visualization and Computer Graphics
FacetAtlas: Multifaceted Visualization for Rich Text Corpora
IEEE Transactions on Visualization and Computer Graphics
Overview of the third international workshop on search and mining user-generated contents
Proceedings of the 20th ACM international conference on Information and knowledge management
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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 a technique that summarises what collections of Twitter users are saying about certain topics over time. As the correct resolution for inspecting the data is unknown in advance, the users are clustered hierarchically over a fixed time interval based on the similarity of their posts. The visualisation technique takes this data structure as its input. Given a topic, it finds the correct resolution of users at each time interval and provides tags to summarise what the collective is discussing. The technique is tested on a large microblogging corpus, consisting of millions of tweets and over a million users.