Are Neighbors Alike? A Semisupervised Probabilistic Collaborative Learning Model for Online Review Spammers Detection
Published Online:23 Oct 2023https://doi.org/10.1287/isre.2022.0047
References
- (2012) Detecting fake medical web sites using recursive trust labeling. ACM Trans. Inform. Systems 30(4):1–36.Crossref, Google Scholar
- (2010) Detecting fake websites: The contribution of statistical learning theory. MIS Quart. 34(3):435–461.Crossref, Google Scholar
- Amazon (2021) Creating a trustworthy reviews experience. Accessed January 1, 2022, https://www.aboutamazon.com/news/how-amazon-works/creating-a-trustworthy-reviews-experience.Google Scholar
- (2022) Know thy context: Parsing contextual information from user reviews for recommendation purposes. Inform. Systems Res. 33(1):179–202.Link, Google Scholar
- (2008) Fast unfolding of communities in large networks. J. Statist. Mech. Theory Experiment 2008(10):P10008.Crossref, Google Scholar
- (2018) Semi-supervised clue fusion for spammer detection in Sina Weibo. Inform. Fusion 44:22–32.Crossref, Google Scholar
- (2005) Preventing shilling attacks in online recommender systems. Proc. 7th Annual ACM Internat. Workshop Web Inform. Data Management (Association for Computing Machinery, New York), 67–74.Google Scholar
- (2017) Detecting cooperative and organized spammer groups in micro-blogging community. Data Mining Knowledge Discovery 31(3):573–605.Crossref, Google Scholar
- (2006) Strategic manipulation of internet opinion forums: Implications for consumers and firms. Management Sci. 52(10):1577–1593.Link, Google Scholar
- (2014) Prediction in economic networks. Inform. Systems Res. 25(2):264–284.Link, Google Scholar
- (2015) Collective spammer detection in evolving multi-relational social networks. Proc. 21th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (Association for Computing Machinery, New York), 1769–1778.Google Scholar
- (2015) Uncovering crowdsourced manipulation of online reviews. Proc. 38th Internat. ACM SIGIR Conf. Res. Development Inform. Retrieval, 233–242.Google Scholar
- (2015) Vocal minority and silent majority: How do online ratings reflect population perceptions of quality? MIS Quart. 39(3):565–589.Crossref, Google Scholar
- (2017) Disconfirmation effect on online rating behavior: A structural model. Inform. Systems Res. 28(3):626–642.Link, Google Scholar
- (2015) Design of consumer review systems and product pricing. Inform. Systems Res. 26(4):714–730.Link, Google Scholar
- (2008) Opinion spam and analysis. Proc. First Internat. Conf. Web Search Data Mining (Association for Computing Machinery, New York), 219–230.Google Scholar
- (2014) Adam: A method for stochastic optimization. Preprint, submitted December 22, https://arxiv.org/abs/1412.6980.Google Scholar
- (2006) Web spam detection with anti-trust rank. Proc. Second Internat. Workshop Adversarial Inform. Retrieval Web (Lehigh University, Bethlehem, PA).Google Scholar
- (2018) Detecting review manipulation on online platforms with hierarchical supervised learning. J. Management Inform. Systems 35(1):350–380.Crossref, Google Scholar
- (2019) Detecting anomalous online reviewers: An unsupervised approach using mixture models. J. Management Inform. Systems 36(4):1313–1346.Crossref, Google Scholar
- (2014) Online product reviews: Implications for retailers and competing manufacturers. Inform. Systems Res. 25(1):93–110.Link, Google Scholar
- (2004) Shilling recommender systems for fun and profit. Proc. 13th Internat. Conf. World Wide Web (Association for Computing Machinery, New York), 393–402.Google Scholar
- (2016) The impact of fake reviews on online visibility: A vulnerability assessment of the hotel industry. Inform. Systems Res. 27(4):940–961.Link, Google Scholar
- (2012) Shilling attack detection—A new approach for a trustworthy recommender system. INFORMS J. Comput. 24(1):117–131.Link, Google Scholar
- (2011) Learning to identify review spam. Walsh T, ed. Proc. 22nd Internat. Joint Conf. Artificial Intelligence (AAAI Press, Palo Alto, CA), 2488–2493.Google Scholar
- (2020) Predicting labor market competition: Leveraging interfirm network and employee skills. Inform. Systems Res. 31(4):1443–1466.Link, Google Scholar
- (2016) Fake it till you make it: Reputation, competition, and yelp review fraud. Management Sci. 62(12):3412–3427.Link, Google Scholar
- (2021) A comprehensive survey on graph anomaly detection with deep learning. IEEE Trans. Knowledge Data Engrg., ePub ahead of print October 8, https://ieeexplore.ieee.org/abstract/document/9565320.Crossref, Google Scholar
- (2006) Model-based collaborative filtering as a defense against profile injection attacks. Proc. 21th AAAI Conf. Artificial Intelligence (AAAI Press, Palo Alto, CA), 1388–1393.Google Scholar
- (2013a) What Yelp fake review filter might be doing? Proc. 7th Internat. Conf. Weblogs Social Media, vol. 7 (AAAI Press, Palo Alto, CA), 409–418.Google Scholar
- (2013b) Spotting opinion spammers using behavioral footprints. Proc. 19th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (Association for Computing Machinery, New York), 632–640.Google Scholar
- (2021) Fake review detection on online e-commerce platforms: A systematic literature review. Data Mining Knowledge Discovery 35(5):1830–1881.Crossref, Google Scholar
- (2014) DeepWalk: Online learning of social representations. Proc. 20th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (Association for Computing Machinery, New York), 701–710.Google Scholar
- (2015) Collective opinion spam detection: Bridging review networks and metadata. Proc. 21th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (Association for Computing Machinery, New York), 985–994.Google Scholar
- (2017) Netspam: A network-based spam detection framework for reviews in online social media. IEEE Trans. Inform. Forensics Security 12(7):1585–1595.Crossref, Google Scholar
- (2021) Creating social contagion through firm-mediated message design: Evidence from a randomized field experiment. Management Sci. 67(2):808–827.Link, Google Scholar
- (2012) Identify online store review spammers via social review graph. ACM Trans. Intelligent Systems Tech. 3(4):61.Crossref, Google Scholar
- (2020) ColluEagle: Collusive review spammer detection using Markov random fields. Data Mining Knowledge Discovery 34(6):1621–1641.Crossref, Google Scholar
- (2017) Semi-supervised classification with graph convolutional networks. Internat. Conf. Learn. Representations (ICLR 2017).Google Scholar
- (2006) Profile injection attack detection for securing collaborative recommender systems. DePaul University CTI Technical Report, 1–47.Google Scholar
- (2005) Identifying link farm spam pages. 14th Internat. Conf. World Wide Web (Association for Computing Machinery, New York), 820–829.Google Scholar
- (2020a) Fake online reviews: Literature review, synthesis, and directions for future research. Decision Support Systems 132:113280.Crossref, Google Scholar
- (2020b) Graph convolutional networks with Markov random field reasoning for social spammer detection. Proc. Conf. AAAI Artificial Intelligence, vol. 34 (AAAI Press, Palo Alto, CA), 1054–1061.Google Scholar
- (2012) HySAD: A semi-supervised hybrid shilling attack detector for trustworthy product recommendation. Proc. 18th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (Association for Computing Machinery, New York), 985–993.Google Scholar
- (2020c) hPSD: A hybrid PU-learning-based spammer detection model for product reviews. IEEE Trans. Cybernetics 50(4):1595–1606.Crossref, Google Scholar
- (2017) An empirical investigation of ecommerce-reputation-escalation-as-a-service. ACM Trans. Web 11(2):1–35.Crossref, Google Scholar
- (2019) Leveraging user-generated content for product promotion: The effects of firm-highlighted reviews. Inform. Systems Res. 30(3):711–725.Link, Google Scholar
- (2014) Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews. MIS Quart. 38:539–560.Crossref, Google Scholar
- (2016) What online reviewer behaviors really matter? Effects of verbal and nonverbal behaviors on detection of fake online reviews. J. Management Inform. Systems 33(2):456–481.Crossref, Google Scholar
- (2006) Exploring both content and link quality for anti-spamming. Sixth IEEE Internat. Conf. Comput. Inform. Tech. (CIT’06) (IEEE, Piscataway, NJ).Google Scholar
- (2023) Spoiled for choice? Personalized recommendation for healthcare decisions: A multiarmed bandit approach. Inform. Systems Res., ePub ahead of print January 19, https://doi.org/10.1287/isre.2022.1191.Link, Google Scholar
- (2010) Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. J. Marketing 74(2):133–148.Crossref, Google Scholar

