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Syst."],"published-print":{"date-parts":[[2020,1,31]]},"abstract":"<jats:p>\u201cUnbiasedness,\u201d which is an important property to ensure that users\u2019 ratings indeed reflect their true evaluations of products, is vital both in shaping consumer purchase decisions and providing reliable recommendations in online rating systems. Recent experimental studies showed that distortions from historical ratings would ruin the unbiasedness of subsequent ratings. How to \u201cdiscover\u201d historical distortions in each single rating (or at the micro-level), and perform the \u201cdebiasing operations\u201d are our main objective. Using 42M real customer ratings, we first show that users either \u201cassimilate\u201d or \u201ccontrast\u201d to historical ratings under different scenarios, which can be further explained by a well-known psychological argument: the \u201cAssimilate-Contrast\u201d theory. This motivates us to propose the Historical Influence Aware Latent Factor Model (HIALF), the \u201cfirst\u201d model for real rating systems to capture and mitigate historical distortions in each single rating. HIALF allows us to study the influence patterns of historical ratings from a modelling perspective, which perfectly matches the assimilation and contrast effects observed in experiments. Moreover, HIALF achieves significant improvements in predicting subsequent ratings and characterizing relationships in ratings. It also contributes to better recommendations, wiser consumer purchase decisions, and deeper understanding of historical distortions in both honest rating and misbehaving rating settings.<\/jats:p>","DOI":"10.1145\/3362651","type":"journal-article","created":{"date-parts":[[2019,10,18]],"date-time":"2019-10-18T12:58:45Z","timestamp":1571403525000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Understanding Assimilation-contrast Effects in Online Rating Systems"],"prefix":"10.1145","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3321-5940","authenticated-orcid":false,"given":"Xiaoying","family":"Zhang","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Xie","sequence":"additional","affiliation":[{"name":"Chongqing University, Shazhengjie, Shapingba, Chongqing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junzhou","family":"Zhao","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John C. 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