Of course, looking only at research papers is a very limited view - we often see that basic understanding of social science can help computer scientists avoid stupid/obvious mistakes in designing social systems. We also see design inspirations coming from social science, which unfortunately is often harder to quantify.
As I have been arguing for a long time (since my time at CollegeClub (1999)), new studies show that we are MUCH more influenced by our PEERS and NOT our FRIENDS. Of course our friends may be a subset of peers, and we may mistake friendship as being the signal (this is the high correlation of influence amongst high schoolers, where our friends ARE our peers).
Therefore, it stands to reason that a multidimensional PEER graph is the valuable signal, NOT a GENERIC social graph!
Peer = multi-dimensional cohort set (any combination of Age, Location, Religion, Education, Occupation, Hobby, etc.)
- Staff Research Scientist, 2011 - present
- PARCArea Manager and Principal Scientist, 2007 - 2011
- Xerox PARCSr. Research Scientist, 1999 - 2006
With 20 patents and over 80 research articles, his most well-known past project is the study of Information Scent --- understanding how users navigate and understand the Web and information environments. Most recently, he leads a group of researchers at PARC to understand the underlying mechanisms in online social systems such as Wikipedia and social tagging sites. He has also worked on information visualization, computational molecular biology, ubicomp, and recommendation/search engines. He has won awards for both teaching and research. In his spare time, Ed is an avid Taekwondo martial artist, photographer, and snowboarder.
In 2012, Ed was the Technical Program Chair for ACM CHI2012 conference, the premier conference on Human-Computer Interaction research.
- University of MinnesotaB.S., minor in Math, 1992 - 1994
- University of MinnesotaM.S., minor in Scientific Computation, 1994 - 1996
- University of MinnesotaPh.D., 1996 - 1999
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