Candidate Talk: Exploring large social networks with matrix-based representations

As people conduct even more of their life electronically, vast new datasets are available for social scientists to analyze. Understanding the structure and evolution of popular online communities such as FaceBook, Flickr or Wikipedia creates new challenges for analysis tools. Information visualization can be a powerful approach to help social scientists both explore these social networks and present their findings to others.
While most of the current systems propose node-link representations, in my PhD I explored matrix-based representations as an alternative. In this talk, I first present my research philosophy: involving users at all stages of the design and providing them with multiple perspectives on their data. I then describe three novel interactive visualizations for exploring and presenting large social networks. I finally conclude with future research directions.

Speaker Details

Nathalie Henry is a joint Ph.D student in Human Computer Interaction and Information Visualization at the Université of Paris-Sud/INRIA, in France and the University of Sydney, in Australia. Her interest lies in the visual exploration of a large quantity of data. Her Ph.D thesis deals with the interactive visualization of social networks. To conduct this work, she used participatory design methods and created interactive visualizations combining and merging different graph representations. She received the Brian Shackel award for her work on augmenting matrix representations.

Date:
Speakers:
Nathalie Henry
Affiliation:
Université of Paris-Sud/INRIA & University of Sydney, in Australia