Trust- and Distrust-Based Recommendations for Controversial Reviews
IEEE Intelligent SystemsPublished 1 January 2011
Patricia Victor, Chris Cornelis, Martine De Cock, Ankur Teredesai
Citations107
SJR quartileQ1
SJR score1.33
SNIP2.01
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
The paper is discussing well-known trust enhanced information filtering techniques for recommending controversial reviews by the recommender systems.
Abstract
By comparing and extending several well-known trust-enhanced techniques for recommending controversial reviews from Epinions.com, the authors provide the first experimental study of using distrust in the recommendation process.
Keywords
Computer ScienceSocial Sciences
IEEE Transactions on Knowledge and Data EngineeringToward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
10,115 Citations2005Gediminas Adomavičius, Alexander Tuzhilin
This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches.
ACM Transactions on Information SystemsEvaluating collaborative filtering recommender systems
5,762 Citations2004Jonathan L. Herlocker, Joseph A. Konstan +2 more
The key decisions in evaluating collaborative filtering recommender systems are reviewed: the user tasks being evaluated, the types of analysis and datasets being used, the ways in which prediction quality is measured, the evaluation of prediction attributes other than quality, and the user-based evaluation of the system as a whole.
Propagation of trust and distrust
1,471 Citations2004R. Guha, Ravi Kumar +2 more
It is shown that a small number of expressed trusts/distrust per individual allows us to predict trust between any two people in the system with high accuracy.
Trust-aware recommender systems
1,181 Citations2007Paolo Massa, Paolo Avesani
This work proposes to replace the step of finding similar users with the use of a trust metric, an algorithm able to propagate trust over the trust network and to estimate a trust weight that can be used in place of the similarity weight.
Trust in recommender systems
860 Citations2005John O’Donovan, Barry Smyth
This paper proposes that the trustworthiness of users must be an important consideration in guiding recommendation and presents two computational models of trust and shows how they can be readily incorporated into standard collaborative filtering frameworks in a variety of ways.
Digital Repository at the University of Maryland (University of Maryland College Park)Computing and applying trust in web-based social networks
839 Citations2005Jennifer Golbeck, James Hendler
It is shown that, in the case where the user's opinion is divergent from the average, the trust-based recommended ratings are more accurate than several other common collaborative filtering techniques.
Comparing Recommendations Made by Online Systems and Friends.
428 Citations2001Rashmi Sinha, Kirsten Swearingen
The hypothesis was that friends would make superior recommendations since they know the user well, and have intimate knowledge of his / her tastes in a number of domains, in contrast to RS, which only have limited, domain-specific knowledge about the users.
Lecture notes in computer scienceGenerating Predictive Movie Recommendations from Trust in Social Networks
399 Citations2006Jennifer Golbeck
This paper presents FilmTrust, a website that uses trust in web-based social networks to create predictive movie recommendations, and shows that these recommendations are more accurate than other techniques when the user's opinions about a film are divergent from the average.
arXiv (Cornell University)The Slashdot Zoo: Mining a Social Network with Negative Edges
394 Citations2017Jérôme Kunegis, Andreas Lommatzsch +1 more
Information Systems FrontiersPropagation Models for Trust and Distrust in Social Networks
343 Citations2005Cai-Nicolas Ziegler, Georg Lausen
This work proposes Appleseed, a novel proposal for local group trust computation that borrows many ideas from spreading activation models in psychology and relates their concepts to trust evaluation in an intuitive fashion.
The slashdot zoo
326 Citations2009Jérôme Kunegis, Andreas Lommatzsch +1 more
The corpus of user relationships of the Slashdot technology news site is analysed and it is shown that the network exhibits multiplicative transitivity which allows algebraic methods based on matrix multiplication to be used.
Designing novel review ranking systems
324 Citations2007Anindya Ghose, Panagiotis G. Ipeirotis
It is shown that subjectivity analysis can give useful clues about the helpfulness of a review and about its impact on sales and the results can have several implications for the market design of online opinion forums.
Modeling and Predicting the Helpfulness of Online Reviews
324 Citations2008Yang Liu, Xiangji Huang +2 more
This paper shows that the helpfulness of a review depends on three important factors: the reviewerpsilas expertise, the writing style of the review, and the timeliness of thereview, and presents a nonlinear regression model for helpfulness prediction.
Fuzzy Sets and SystemsGradual trust and distrust in recommender systems
197 Citations2008Patricia Victor, Chris Cornelis +2 more
This paper advocates the use of a trust model in which trust scores are (trust,distrust)-couples, drawn from a bilattice that preserves valuable trust provenance information including gradual trust, distrust, ignorance, and inconsistency.
A trust-enhanced recommender system application
186 Citations2005Paolo Avesani, Paolo Massa +1 more
This paper claims that trustworthiness is a user centered notion that requires the computation of personalized metrics, and presents an open information exchange architecture that makes use of Semantic Web formats to guarantee interoperability between ski mountaineering communities.
Human-computer interaction seriesTrust Metrics in Recommender Systems
136 Citations2009Paolo Massa, Paolo Avesani
This work proposes the use of a trust metric, an algorithm able to propagate trust over the trust network in order to find users that can be trusted by the active user, so that trust is able to alleviate the cold start problem and other weaknesses that beset Collaborative Filtering Recommender Systems.
Lecture notes in computer scienceExploring Different Types of Trust Propagation
125 Citations2006Audun Jøsang, Stephen Marsh +1 more
This paper investigates possible formal models that can be implemented using belief reasoning based on subjective logic for trust propagation, with the purpose of enhancing the quality of those communities of people, organisations and software agents.
Multiple Relationship Types in Online Communities and Social Networks.
52 Citations2008Tad Hogg, Dennis M. Wilkinson +2 more
An empirical study of an online political forum where users engage in content creation, voting, and discussion, and demonstrates significant structural differences among the networks, indicating different uses for each.
Proceedings of the International AAAI Conference on Web and Social MediaA Comparative Analysis of Trust-Enhanced Recommenders for Controversial Items
28 Citations2009Patricia Victor, Chris Cornelis +2 more
This paper formalizes the concept of CIs in RSs, and introduces a new algorithm that maximizes the synergy between CF and its trust-based variants, and shows that the new algorithm outperforms other trust- based techniques in generating rating predictions for CIs.
AI CommunicationsTrust-based recommendations for documents
9 Citations2008Claudia Heß, Christoph Schlieder
Trust-enhanced visibility measures for measuring the quality and the importance of documents and evaluate them in simulation studies are developed.
