User Participation and Honesty in Online Rating Systems: What a Social Network Can Do

Alan Davoust; Babak Esfandiari

User Participation and Honesty in Online Rating Systems: What a Social Network Can Do

Alan Davoust, Babak Esfandiari

School of Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	The Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities: Technical Report WS-16-09
Publisher	AAAI Press
Pages	477-483
Number of pages	7
ISBN (Print)	978-1-57735-759-9
Publication status	Published - Jul 2016
Event	Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities - Phoenix, United States Duration: 12 Feb 2016 → 13 Feb 2016 https://www.aaai.org/Library/Workshops/ws16-09.php

Conference

Conference	Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities
Country/Territory	United States
City	Phoenix
Period	12/02/16 → 13/02/16
Internet address	https://www.aaai.org/Library/Workshops/ws16-09.php

Access to Document

12567-57472-1-PBFinal published version, 562 KB

http://www.aaai.org/ocs/index.php/WS/AAAIW16/paper/view/12567

Cite this

@inproceedings{46b87a2fed96430c868cfddb709e5e50,

title = "User Participation and Honesty in Online Rating Systems: What a Social Network Can Do",

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.",

author = "Alan Davoust and Babak Esfandiari",

year = "2016",

month = jul,

language = "English",

isbn = "978-1-57735-759-9",

pages = "477--483",

booktitle = "The Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities: Technical Report WS-16-09",

publisher = "AAAI Press",

note = "Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities ; Conference date: 12-02-2016 Through 13-02-2016",

url = "https://www.aaai.org/Library/Workshops/ws16-09.php",

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Davoust, A & Esfandiari, B 2016, User Participation and Honesty in Online Rating Systems: What a Social Network Can Do. in The Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities: Technical Report WS-16-09. AAAI Press, pp. 477-483, Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities, Phoenix, Arizona, United States, 12/02/16. <http://www.aaai.org/ocs/index.php/WS/AAAIW16/paper/view/12567>

User Participation and Honesty in Online Rating Systems: What a Social Network Can Do. / Davoust, Alan; Esfandiari, Babak.

The Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities: Technical Report WS-16-09. AAAI Press, 2016. p. 477-483.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - User Participation and Honesty in Online Rating Systems: What a Social Network Can Do

AU - Davoust, Alan

AU - Esfandiari, Babak

PY - 2016/7

Y1 - 2016/7

N2 - 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.

AB - 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.

M3 - Conference contribution

SN - 978-1-57735-759-9

SP - 477

EP - 483

BT - The Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities: Technical Report WS-16-09

PB - AAAI Press

T2 - Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Incentives and Trust in Electronic Communities

Y2 - 12 February 2016 through 13 February 2016

ER -

User Participation and Honesty in Online Rating Systems: What a Social Network Can Do

Abstract

Conference

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