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BEGIN:VEVENT
DTSTAMP:20260417T172418Z
DTSTART;VALUE=DATE-TIME:20240508T130000
DTEND;VALUE=DATE-TIME:20240508T140000
SUMMARY:CAGE-AMES Workshop - Adam Di Lizia (PGR)
TZID:Europe/London
UID:20240508-8a1785d78eeb79d1018eeca1df170b7d@warwick.ac.uk
CREATED:20240503T141257Z
DESCRIPTION:Title: Social Influence in Online Reviews: Evidence from the 
 Steam Store Abstract: How good are reviews as signals of product quality
  for consumers? Using a data-set derived from the popular Steam gaming p
 latform I investigate the ‘priming’ of quality judgements as based on pr
 e-existing consumer assessments. A policy reform on Steam in 2019 change
 d the average level of exposure to previous consumer quality ratings\, w
 ith this randomly occurring within a game and reviewer’s life cycle. I f
 ind that removing the exposure of a reviewer to a product’s average rati
 ng leads to a 35% drop in the dependency of their review on such a ratin
 g. This is not driven by selection effects\, and is robust to a wide ran
 ge of alternate specifications and measures. The effect is heavily asymm
 etric: negativity compounds to inflate the gap between poorly-rated and 
 well rated games. This is driven by users who are less experienced both 
 within and across games. Finally\, using estimates of owner data\, I run
  a simple structural model of game choice based on rating. A 1% increase
  to product rating is equivalent to a 2.5 dollar sale price reduction\, 
 suggesting this effect has large implications for buyers and sellers.
LOCATION:S2.79
CATEGORIES:CAGE-AMES Workshop
LAST-MODIFIED:20240503T141257Z
ORGANIZER;CN=Gill Gudger:
END:VEVENT
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