GuessTheKarma: A Game to Assess Social Rating Systems

09/03/2018 ∙ by Maria Glenski, et al. ∙ 0

Popularity systems, like Twitter retweets, Reddit upvotes, and Pinterest pins have the potential to guide people toward posts that others liked. That, however, creates a feedback loop that reduces their informativeness: items marked as more popular get more attention, so that additional upvotes and retweets may simply reflect the increased attention and not independent information about the fraction of people that like the items. How much information remains? For example, how confident can we be that more people prefer item A to item B if item A had hundreds of upvotes on Reddit and item B had only a few? We investigate using an Internet game called GuessTheKarma that collects independent preference judgments (N=20,674) for 400 pairs of images, approximately 50 per pair. Unlike the rating systems that dominate social media services, GuessTheKarma is devoid of social and ranking effects that influence ratings. Overall, Reddit scores were not very good predictors of the true population preferences for items as measured by GuessTheKarma: the image with higher score was preferred by a majority of independent raters only 68 time. However, when one image had a low score and the other was one of the highest scoring in its subreddit, the higher scoring image was preferred nearly 90 counts for the images were poor predictors except when there were orders of magnitude differences between the pairs. We conclude that popularity systems marked by feedback loops may convey a strong signal about population preferences, but only when comparing items that received vastly different popularity scores.



There are no comments yet.


This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.