Joint Colloquium Distinguished Lecture Series

To friend and to trust: eliciting truthful and useful ratings online

lada adamic

Wednesday, September 14, 2011
306 Soda Hall (HP Auditorium)
4:00 - 5:00 pm

Lada Adamic
Professor, School of Information and the Center for the Study of Complex Systems, University of Michigan

Downloadable pdf


Online rating and reputation systems have shown themselves to be essential for filtering content, building trust, and fostering communities. However, these ratings should not be taken at face value. When individuals submit ratings online, especially ratings of other people, they are being asked to quantify inherently subjective feelings.

To complicate matters, they may formulate their ratings differently if these are shown to others, and if those others can reciprocate. In this talk I will present two studies that combine data analysis of several online data sets. For one such system,, I will discuss findings from a large- scale survey and in-depth interviews to examine from multiple angles the challenges that users have in providing useful and truthful ratings. We find, for example, that the potential to reciprocate produces higher and more correlated ratings than when individuals are unable to see how others rated them. Ratings further can depend on the gender, age and nationalities of the raters and ratees.

All of these findings indicate that ratings should not be taken at face value without considering social nuances.


Lada A. Adamic is an associate professor in the School of Information and the Center for the Study of Complex Systems at the University of Michigan. She is also affiliated with EECS. Her research interests center on information dynamics in networks: how information diffuses, how it can be found, and how it influences the evolution of a network's structure. Her projects have included identifying expertise in online question and answer forums, studying the dynamics of viral marketing, and characterizing the structure in blogs and other online communities. She has received an NSF CAREER award, and best paper awards from Hypertext'08, ICWSM'10 and '11, and the most influential paper of the decade award from Web Intelligence'11.

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