Collaborative recommendation: A robustness analysis
ACM Transactions on Internet Technology (TOIT)
Computing trusted authority scores in peer-to-peer web search networks
AIRWeb '07 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
Unsupervised retrieval of attack profiles in collaborative recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Detecting reviewer bias through web-based association mining
Proceedings of the 2nd ACM workshop on Information credibility on the web
User generated content: how good is it?
Proceedings of the 3rd workshop on Information credibility on the web
Recommender systems: attack types and strategies
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Mechanisms for making crowds truthful
Journal of Artificial Intelligence Research
Ranking Comments on the Social Web
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Learning to recommend helpful hotel reviews
Proceedings of the third ACM conference on Recommender systems
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
Detecting collective attention spam
Proceedings of the 2nd Joint WICOW/AIRWeb Workshop on Web Quality
Building and managing reputation in the environment of Chinese e-commerce: a case study on Taobao
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Identify Online Store Review Spammers via Social Review Graph
ACM Transactions on Intelligent Systems and Technology (TIST)
Review quality aware collaborative filtering
Proceedings of the sixth ACM conference on Recommender systems
In search of a gold standard in studies of deception
EACL 2012 Proceedings of the Workshop on Computational Approaches to Deception Detection
NordSec'12 Proceedings of the 17th Nordic conference on Secure IT Systems
Simultaneously detecting fake reviews and review spammers using factor graph model
Proceedings of the 5th Annual ACM Web Science Conference
Campaign extraction from social media
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
| Hi-index | 0.00 |
Assessing the trustworthiness of reviews is a key issue for the maintainers of opinion sites such as TripAdvisor. In this paper we propose a distortion criterion for assessing the impact of methods for uncovering suspicious hotel reviews in TripAdvisor. The principle is that dishonest reviews will distort the overall popularity ranking for a collection of hotels. Thus a mechanism that deletes dishonest reviews will distort the popularity ranking significantly, when compared with the removal of a similar set of reviews at random. This distortion can be quantified by comparing popularity rankings before and after deletion, using rank correlation. We present an evaluation of this strategy in the assessment of shill detection mechanisms on a dataset of hotel reviews collected from TripAdvisor.