{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T02:35:31Z","timestamp":1784342131116,"version":"3.55.0"},"reference-count":39,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:00:00Z","timestamp":1705536000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJWIS"],"published-print":{"date-parts":[[2024,2,23]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Users often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>In this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users\u2019 credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>Theoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ijwis-12-2023-0247","type":"journal-article","created":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T02:03:48Z","timestamp":1705457028000},"page":"176-194","source":"Crossref","is-referenced-by-count":6,"title":["User credibility evaluation for reputation measurement of online service"],"prefix":"10.1108","volume":"20","author":[{"given":"Yahan","family":"Xiong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodong","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2024,1,18]]},"reference":[{"issue":"1\/4","key":"key2024022204050369000_ref001","first-page":"1","article-title":"A simulation software for the evaluation of vulnerabilities in reputation management systems","volume":"37","year":"2021","journal-title":"ACM Transactions on Computer Systems"},{"key":"key2024022204050369000_ref002","doi-asserted-by":"crossref","first-page":"35321","DOI":"10.1109\/ACCESS.2022.3163246","article-title":"CBiLSTM: a hybrid deep learning model for efficient reputation assessment of cloud services","volume":"10","year":"2022","journal-title":"IEEE Access"},{"issue":"2","key":"key2024022204050369000_ref003","first-page":"340","article-title":"An iterative method for calculating robust rating scores","volume":"26","year":"2014","journal-title":"IEEE Transactions on Parallel and Distributed Systems"},{"key":"key2024022204050369000_ref004","first-page":"35","article-title":"The Netflix prize","year":"2007"},{"key":"key2024022204050369000_ref005","first-page":"41","article-title":"Ranking online services by aggregating ordinal preferences","volume-title":"Web-Age Information Management: WAIM 2016 International Workshops, MWDA, SDMMW, and SemiBDMA","year":"2016"},{"issue":"2\/3","key":"key2024022204050369000_ref006","first-page":"381","article-title":"Robust ordinal regression in preference learning and ranking","volume":"93","year":"2013","journal-title":"Machine Learning"},{"issue":"3","key":"key2024022204050369000_ref007","doi-asserted-by":"crossref","first-page":"483","DOI":"10.3390\/electronics9030483","article-title":"Sentiment analysis based on deep learning: a comparative study","volume":"9","year":"2020","journal-title":"Electronics"},{"key":"key2024022204050369000_ref008","article-title":"Eliciting truthful information with the peer truth serum","volume-title":"ACM conference on Economics and Computation (EC\u201914)","year":"2014"},{"issue":"4","key":"key2024022204050369000_ref009","first-page":"1076","article-title":"GroupTrust: dependable trust management","volume":"28","year":"2016","journal-title":"IEEE Transactions on Parallel and Distributed Systems"},{"key":"key2024022204050369000_ref010","first-page":"658","article-title":"Feature analysis for fake review detection through supervised classification","year":"2017"},{"issue":"4","key":"key2024022204050369000_ref011","first-page":"1054","article-title":"Reputation measurement for online services based on dominance relationships","volume":"14","year":"2018","journal-title":"IEEE Transactions on Services Computing"},{"key":"key2024022204050369000_ref012","first-page":"248","article-title":"Ordinal preferences driven reputation measurement for online services with user incentive","year":"2020"},{"key":"key2024022204050369000_ref014","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1016\/j.physa.2017.01.055","article-title":"Evaluating user reputation in online rating systems via an iterative group-based ranking method","volume":"473","year":"2017","journal-title":"Physica A: Statistical Mechanics and Its Applications"},{"key":"key2024022204050369000_ref015","first-page":"507","article-title":"Trick or treat: putting peer prediction to the test","year":"2014"},{"issue":"2","key":"key2024022204050369000_ref013","doi-asserted-by":"crossref","first-page":"28003","DOI":"10.1209\/0295-5075\/110\/28003","article-title":"Group-based ranking method for online rating systems with spamming attacks","volume":"110","year":"2015","journal-title":"EPL (Europhysics Letters)"},{"issue":"4","key":"key2024022204050369000_ref016","first-page":"2439","article-title":"A survey on web service QoS prediction methods","volume":"15","year":"2020","journal-title":"IEEE Transactions on Services Computing"},{"issue":"4","key":"key2024022204050369000_ref017","first-page":"1","article-title":"The movielens datasets: history and context","volume":"5","year":"2015","journal-title":"Acm Transactions on Interactive Intelligent Systems (Tiis)"},{"key":"key2024022204050369000_ref018","first-page":"15","article-title":"An iterative deviation-based ranking method to evaluate user reputation in online rating systems","year":"2021"},{"key":"key2024022204050369000_ref019","article-title":"Using attentive temporal gnn for dynamic trust assessment in the presence of malicious entities","volume-title":"available at SSRN","year":"2023"},{"key":"key2024022204050369000_ref020","first-page":"2502","article-title":"The beta reputation system","year":"2002"},{"key":"key2024022204050369000_ref021","first-page":"1236","article-title":"MOOCs completion rates and possible methods to improve retention-A literature review","volume-title":"World Conference on Educational Multimedia, Hypermedia and Telecommunications, Association for the Advancement of Computing in Education (AACE)","year":"2014"},{"issue":"6","key":"key2024022204050369000_ref022","doi-asserted-by":"crossref","first-page":"68004","DOI":"10.1209\/0295-5075\/121\/68004","article-title":"Deviation-based spam-filtering method via stochastic approach","volume":"121","year":"2018","journal-title":"EPL (Europhysics Letters)"},{"issue":"2","key":"key2024022204050369000_ref023","first-page":"310","article-title":"Enabling trustworthy service evaluation in service-oriented mobile social networks","volume":"25","year":"2013","journal-title":"IEEE Transactions on Parallel and Distributed Systems"},{"issue":"4","key":"key2024022204050369000_ref024","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.rehab.2014.03.002","article-title":"The effectiveness of semantic feature analysis: an evidence-based systematic review","volume":"57","year":"2014","journal-title":"Annals of Physical and Rehabilitation Medicine"},{"issue":"9","key":"key2024022204050369000_ref025","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.1287\/mnsc.1050.0379","article-title":"Eliciting informative feedback: the peer-prediction method","volume":"51","year":"2005","journal-title":"Management Science"},{"issue":"6146","key":"key2024022204050369000_ref026","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1126\/science.1240466","article-title":"Social influence bias: a randomized experiment","volume":"341","year":"2013","journal-title":"Science"},{"issue":"1","key":"key2024022204050369000_ref027","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/s13278-021-00776-6","article-title":"A review on sentiment analysis and emotion detection from text","volume":"11","year":"2021","journal-title":"Social Network Analysis and Mining"},{"issue":"1","key":"key2024022204050369000_ref028","first-page":"1","article-title":"A survey on the usage of eye-tracking in computer programming","volume":"51","year":"2018","journal-title":"ACM Computing Surveys"},{"issue":"1","key":"key2024022204050369000_ref029","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1609\/aaai.v27i1.8677","article-title":"A robust Bayesian truth serum for non-binary signals","volume":"27","year":"2013","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"key2024022204050369000_ref030","article-title":"Incentives for truthful information elicitation of continuous signals","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","year":"2014"},{"key":"key2024022204050369000_ref031","first-page":"179","article-title":"Informed truthfulness in multi-task peer prediction","volume-title":"ACM Conference on Economics and Computation","year":"2016"},{"key":"key2024022204050369000_ref032","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.dss.2015.04.009","article-title":"A survey on trust and reputation models for web services: Single, composite, and communities","volume":"74","year":"2015","journal-title":"Decision Support Systems"},{"issue":"11","key":"key2024022204050369000_ref033","doi-asserted-by":"crossref","first-page":"2126","DOI":"10.3724\/SP.J.1016.2010.02126","article-title":"Research on context-awareness mobile SNS service selection mechanism","volume":"33","year":"2010","journal-title":"Chinese Journal of Computers"},{"issue":"7","key":"key2024022204050369000_ref034","doi-asserted-by":"crossref","first-page":"5731","DOI":"10.1007\/s10462-022-10144-1","article-title":"A survey on sentiment analysis methods, applications, and challenges","volume":"55","year":"2022","journal-title":"Artificial Intelligence Review"},{"key":"key2024022204050369000_ref037","first-page":"245","article-title":"Elicitability and knowledge-free elicitation with peer prediction","year":"2014"},{"issue":"2","key":"key2024022204050369000_ref035","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1109\/MGRS.2022.3145854","article-title":"Artificial intelligence for remote sensing data analysis: a review of challenges and opportunities","volume":"10","year":"2022","journal-title":"IEEE Geoscience and Remote Sensing Magazine"},{"issue":"7","key":"key2024022204050369000_ref036","first-page":"1631","article-title":"Commtrust: computing multi-dimensional trust by mining e-commerce feedback comments","volume":"26","year":"2013","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"3","key":"key2024022204050369000_ref038","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1109\/TMM.2016.2515362","article-title":"User-service rating prediction by exploring social users' rating behaviors","volume":"18","year":"2016","journal-title":"IEEE Transactions on Multimedia"},{"issue":"4","key":"key2024022204050369000_ref039","doi-asserted-by":"crossref","first-page":"48002","DOI":"10.1209\/0295-5075\/94\/48002","article-title":"A robust ranking algorithm to spamming","volume":"94","year":"2011","journal-title":"EPL (Europhysics Letters)"}],"container-title":["International Journal of Web Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJWIS-12-2023-0247\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJWIS-12-2023-0247\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T22:24:31Z","timestamp":1753395871000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/ijwis\/article\/20\/2\/176-194\/1215300"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,18]]},"references-count":39,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,1,18]]},"published-print":{"date-parts":[[2024,2,23]]}},"alternative-id":["10.1108\/IJWIS-12-2023-0247"],"URL":"https:\/\/doi.org\/10.1108\/ijwis-12-2023-0247","relation":{},"ISSN":["1744-0084","1744-0084"],"issn-type":[{"value":"1744-0084","type":"print"},{"value":"1744-0084","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,18]]}}}