Title :
pieTime: Visualizing Communication Patterns
Author :
Ng, Tiffany ; Zhao, Ou Jie ; Cosley, Dan
Author_Institution :
Inf. Sci. Dept., Cornell Univ., Ithaca, NY, USA
Abstract :
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.
Keywords :
data visualisation; pattern classification; recording; social networking (online); aggregate patterns; aggregated behavioral data; communication activity; communication patterns visualization; conversation visualization; life logging; pieTime; storytelling; Aggregates; Data visualization; Electronic mail; Focusing; Media; Prototypes; Reflection; information visualization; lifelogging; reflection;
Conference_Titel :
Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 2011 IEEE Third International Conference on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4577-1931-8
DOI :
10.1109/PASSAT/SocialCom.2011.90