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pieTime: Visualizing Communication Patterns

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3 Author(s)
Tiffany Ng ; Inf. Sci. Dept., Cornell Univ., Ithaca, NY, USA ; Ou Jie Zhao ; Dan Cosley

This paper explores how aggregated behavioral data might help people reflect on patterns in their lives using pie Time, a visualization that presents communication activity aggregated at levels from hours in a day to months in a year. pie Time builds on recent work in conversation visualization and life logging by focusing on rhythms rather than details and supporting reflection across different media. An evaluation with 15 people supports findings from prior work about the importance of particular details and storytelling in tools that support reflection, even when the design goals emphasize higher-level patterns. Still, aggregate patterns provide additional insight into personal behavior, suggesting that systems that integrate both particulars and patterns may be especially valuable, especially when they also help people build and manage their identities.

Published in:

Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 2011 IEEE Third International Conference on

Date of Conference:

9-11 Oct. 2011