CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Graph Visualization and Navigation in Information Visualization: A Survey
IEEE Transactions on Visualization and Computer Graphics
Studying cooperation and conflict between authors with history flow visualizations
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
SoftVis '05 Proceedings of the 2005 ACM symposium on Software visualization
Line graph explorer: scalable display of line graphs using Focus+Context
Proceedings of the working conference on Advanced visual interfaces
Talk Before You Type: Coordination in Wikipedia
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
NetLens: iterative exploration of content-actor network data
Information Visualization
Lifting the veil: improving accountability and social transparency in Wikipedia with wikidashboard
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
LiveRAC: interactive visual exploration of system management time-series data
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Visualizing activity on wikipedia with chromograms
INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction - Volume Part II
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To increase its credibility and preserve the trust of its readers. Wikipedia needs to ensure a good quality of its articles. To that end, it is critical for Wikipedia administrators to be aware of contributors' editing activity to monitor vandalism, encourage reliable contributors to work on specific articles, or find mentors for new contributors. In this paper, we present iChase, a novel interactive visualization tool to provide administrators with better awareness of editing activities on Wikipedia. Unlike the currently used visualizations that provide only page-centric information. iChase visualizes the trend of activities for two entity types; articles and contributors. iChase is based on two heatmaps (one for each entity type) synchronized to one timeline. It allows users to interactively explore the history of changes by drilling down into specific articles and contributors, or time points to access the details of the changes. We also present a case study to illustrate how iChase can be used to monitor editing activities of Wikipedia authors, as well as a usability study. We conclude by discussing the strengths and weaknesses of iChase.