Professor Sinan Aral and his coauthors Lev Mucknik of the Hebrew University of Jerusalem and Sean J. Taylor of NYU Stern have published a new study in the journal, Science. Their research studies the effects of prior user reviews on individual decision making and rating behavior.
Excerpt from The New York Times:
If you “like” this article on a site like Facebook, somebody who reads it is more likely to approve of it, even if the reporting and writing are not all that great.
But surprisingly, an unfair negative reaction will not spur others to dislike the article. Instead, a thumbs-down view will soon be counteracted by thumbs up from other readers.
Those are the implications of new research looking at the behavior of thousands of people reading online comments, scientists reported Friday in the journal Science. A positive nudge, they said, can set off a bandwagon of approval.
“Hype can work,” said one of the researchers, Sinan K. Aral, a professor of information technology and marketing at the Massachusetts Institute of Technology, “and feed on itself as well.”
Read the full article at nytimes.com
Abstract of “Social Influence Bias: A Randomized Experiment”
Our society is increasingly relying on the digitized, aggregated opinions of others to make decisions. We therefore designed and analyzed a large-scale randomized experiment on a social news aggregation Web site to investigate whether knowledge of such aggregates distorts decision-making. Prior ratings created significant bias in individual rating behavior, and positive and negative social influences created asymmetric herding effects. Whereas negative social influence inspired users to correct manipulated ratings, positive social influence increased the likelihood of positive ratings by 32% and created accumulating positive herding that increased final ratings by 25% on average. This positive herding was topic-dependent and affected by whether individuals were viewing the opinions of friends or enemies. A mixture of changing opinion and greater turnout under both manipulations together with a natural tendency to up-vote on the site combined to create the herding effects. Such findings will help interpret collective judgment accurately and avoid social influence bias in collective intelligence in the future.
Read the report at sciencemag.org