• DocumentCode
    2776177
  • Title

    pieTime: Visualizing Communication Patterns

  • Author

    Ng, Tiffany ; Zhao, Ou Jie ; Cosley, Dan

  • Author_Institution
    Inf. Sci. Dept., Cornell Univ., Ithaca, NY, USA
  • fYear
    2011
  • fDate
    9-11 Oct. 2011
  • Firstpage
    720
  • Lastpage
    723
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • 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
  • Type

    conf

  • DOI
    10.1109/PASSAT/SocialCom.2011.90
  • Filename
    6113204