@inproceedings{davoust_user_2016,

title = {User participation and honesty in online rating systems: What a social network can do},

author = {A. Davoust and B. Esfandiari},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021919921&partnerID=40&md5=6a33a1ab6d3b6ddd037240f4f664b6fe},

isbn = {978-1-57735-759-9},

year  = {2016},

date = {2016-01-01},

booktitle = {AAAI Workshop - Technical Report},

volume = {WS-16-01 - WS-16-15},

pages = {477–483},

publisher = {AI Access Foundation},

abstract = {An important problem with online communities in general, and online rating systems in particular, is uncooperative behavior: lack of user participation, dishonest contributions. This may be due to an incentive structure akin to a Prisoners' Dilemma (PD). We show that introducing an explicit social network to PD games fosters cooperative behavior, and use this insight to design a new aggregation technique for online rating systems. Using a dataset of ratings from Yelp, we show that our aggregation technique outperforms Yelp's proprietary filter, as well as baseline techniques from recommender systems. Copyright © 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org).},

keywords = {Aggregation techniques, Artificial intelligence, Behavioral research, Big data, Co-operative behaviors, Cognitive systems, Computer games, Computer programming, Computer systems programming, Data mining, Hybrid systems, Incentive structure, On-line communities, Online rating systems, Online systems, Population statistics, Prisoners' Dilemma, Rating, Social networking (online), User participation},

pubstate = {published},

tppubtype = {inproceedings}

}