Generating summaries and visualization for large collections of geo-referenced photographs
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
TIMELINES: Tag clouds and the case for vernacular visualization
interactions - Changing energy use through design
Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration
INTERACT '09 Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I
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
Twitter under crisis: can we trust what we RT?
Proceedings of the First Workshop on Social Media Analytics
Space-time dynamics of topics in streaming text
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Representing and visualizing folksonomies as graphs: a reference model
Proceedings of the International Working Conference on Advanced Visual Interfaces
Spatiotemporal anomaly detection through visual analysis of geolocated Twitter messages
PACIFICVIS '12 Proceedings of the 2012 IEEE Pacific Visualization Symposium
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The vast amount of contents posted to microblogging services each day offers a rich source of information for analytical tasks. The aggregated posts provide a broad sense of the informal conversations complementing other media. However, analyzing the textual content is challenging due to its large volume, heterogeneity, and time-dependence. In this paper, we exploit the idea of tag clouds to visually analyze microblog content. As a major contribution, tag clouds are extended by an interactive visualization technique that we refer to as time-varying co-occurrence highlighting. It combines colored histograms with visual highlighting of co-occurrences, thus allowing for a time-dependent analysis of term relations. An example dataset of Twitter posts illustrates the applicability and usefulness of the approach.