TY - GEN
T1 - Combating crowdsourced review manipulators
T2 - 11th ACM International Conference on Web Search and Data Mining, WSDM 2018
AU - Kaghazgaran, Parisa
AU - Caverlee, James
AU - Squicciarini, Anna
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/2/2
Y1 - 2018/2/2
N2 - We propose a system called TwoFace to uncover crowdsourced review manipulators who target online review systems. A unique feature of TwoFace is its three-phase framework: (i) in the first phase, we intelligently sample actual evidence of manipulation (e.g., review manipulators) by exploiting low moderation crowdsourcing platforms that reveal evidence of strategic manipulation; (ii) we then propagate the suspiciousness of these seed users to identify similar users through a random walk over a "suspiciousness" graph; and (iii) finally, we uncover (hidden) distant users who serve structurally similar roles by mapping users into a low-dimensional embedding space that captures community structure. Altogether, the TwoFace system recovers 83% to 93% of all manipulators in a sample from Amazon of 38,590 reviewers, even when the system is seeded with only a few samples from malicious crowdsourcing sites.
AB - We propose a system called TwoFace to uncover crowdsourced review manipulators who target online review systems. A unique feature of TwoFace is its three-phase framework: (i) in the first phase, we intelligently sample actual evidence of manipulation (e.g., review manipulators) by exploiting low moderation crowdsourcing platforms that reveal evidence of strategic manipulation; (ii) we then propagate the suspiciousness of these seed users to identify similar users through a random walk over a "suspiciousness" graph; and (iii) finally, we uncover (hidden) distant users who serve structurally similar roles by mapping users into a low-dimensional embedding space that captures community structure. Altogether, the TwoFace system recovers 83% to 93% of all manipulators in a sample from Amazon of 38,590 reviewers, even when the system is seeded with only a few samples from malicious crowdsourcing sites.
UR - http://www.scopus.com/inward/record.url?scp=85046902746&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046902746&partnerID=8YFLogxK
U2 - 10.1145/3159652.3159726
DO - 10.1145/3159652.3159726
M3 - Conference contribution
AN - SCOPUS:85046902746
T3 - WSDM 2018 - Proceedings of the 11th ACM International Conference on Web Search and Data Mining
SP - 306
EP - 314
BT - WSDM 2018 - Proceedings of the 11th ACM International Conference on Web Search and Data Mining
PB - Association for Computing Machinery, Inc
Y2 - 5 February 2018 through 9 February 2018
ER -