Title :
Is the Crowd´s Wisdom Biased? A Quantitative Analysis of Three Online Communities
Author :
Kostakos, Vassilis
Author_Institution :
Dept. of Math. & Eng., Univ. of Madeira, Madeira, Portugal
Abstract :
We present a study of user voting on three websites: Imdb, Amazon and BookCrossings. Here we report on an expert evaluation of the voting mechanisms of each website and a quantitative data analysis of userspsila aggregate voting behavior. Our results suggest that the websites with higher barrier to vote introduce a relatively high number of one-off voters, and they appear to attract mostly experts. We also find that one-off voters tend to vote on popular items, while experts mostly vote for obscure, low-rated items. We conclude with design suggestions to address the ldquowisdom of the crowdrdquo bias.
Keywords :
Web sites; data analysis; interactive programming; user interfaces; Web sites; data analysis; expert evaluation; online communities; quantitative analysis; user voting; Aggregates; Data analysis; Databases; Displays; Feedback; Graphics; Histograms; Mathematics; Motion pictures; Voting;
Conference_Titel :
Computational Science and Engineering, 2009. CSE '09. International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-5334-4
Electronic_ISBN :
978-0-7695-3823-5
DOI :
10.1109/CSE.2009.491