[Solomonov Seminar] 264. Solomonov seminar

[Marko Grobelnik]

V petek 11. julija bo ob 13h v Veliki predavalnici IJS 264. Solomonov 
seminar. Velika predavalnica je v prvem nadstropju glavne stavbe IJS. 
Posnetki preteklih seminarjev so na http://videolectures.net/solomon/

Tokrat bo nas bivsi sodelavec Ruben Sipos, ki sedaj koncuje doktorat na 
univerzi Corel, predstavil analizo uporabniskih komentarjev na Amazonu-u.

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Ruben Sipos, Cornel University:

Was This Review Helpful to You? It Depends!
Context and Voting Patterns in Online Content

When a website hosting user-generated content asks users
a straightforward question -- "Was this content helpful?"
with one "Yes" and one "No" button as the two possible
answers -- one might expect to get a straightforward answer.
In this paper, we explore how users respond to this
question and find that their responses are not quite
straight-forward after all. Using data from Amazon product reviews,
we present evidence that users do not make absolute, independent
voting decisions based on individual review quality
alone. Rather, whether users vote at all, as well as the polarity
of their vote for any given review, depends on the
context in which they view it -- reviews receive a larger
overall number of votes when they are 'misranked', and the
polarity of votes becomes more positive/negative when the
review is ranked lower/higher than it deserves. We distill
these empirical 
findings into a new probabilistic model of
rating behavior that includes the dependence of rating decisions
on context. Understanding and formally modeling
voting behavior is crucial for designing learning mechanisms
and algorithms for review ranking, and we conjecture that
many of our findings also apply to user behavior in other
online content-rating settings.