Anthropomorphic visualization : depicting participants in online spaces using the human form

Abstract

Anthropomorphic visualization is a new approach to presenting information about participants in online spaces using the human form as the basis for the visualization. Various data about an individual's online behavior are mapped to different parts of a humanoid yet abstract form. I hypothesized that using a humanoid form to visualize data about people in online social spaces could serve two purposes simultaneously: communicate statistics about the individuals and evoke a social response. Using the human form in this way has both benefits and drawbacks. Users can quickly scan a set of humanoid representations and get a sense of the character of a group, and may respond socially to the other participants in the group. However, the information we are able to represent is somewhat limited, and a humanoid representation style might lead users to make incorrect assumptions about the people being represented. To investigate these tradeoffs, I created a test- bed application that visualized data from messages written in Usenet newsgroups. I conducted user studies to evaluate how users interpreted the data from the visualizations and responded to messages shown with visualizations. In this thesis, I discuss the challenges of designing effective anthropomorphic visualizations and offer guidelines to consider when using the human form to visualize information about participants in online conversations.