2013年8月12日月曜日

Social Influence Bias: A Randomized Experiment

Lev Muchnik, Sinan Aral, Sean J. Taylor
Science 9 August 2013:
Vol. 341 no. 6146 pp. 647-651

口コミサイト(例:食べログ、Yelpなど)のように「みんなの意見を蓄積する」ことは「評価におけるバイアス」を減少させるのか?
実際のWEBサイトのデータを解析。
結果は、悪い方へのバイアスはみんなの意見を集計することで解消出来るが、良い方へのバイアスは解消出来ない。
個々人の意見が「他人の良い評価」に引っ張られて(悪い評価には引っ張られない)、ポジティブ・フィードバックがかかるから。

含意は「食べログなどでは、良い評価はバイアスがかかっている可能性あり」ということ?

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.

0 件のコメント:

コメントを投稿