{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T05:18:14Z","timestamp":1769750294231,"version":"3.49.0"},"reference-count":87,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T00:00:00Z","timestamp":1675728000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2023,7,31]]},"abstract":"<jats:p>Recently, privacy issues in web services that rely on users\u2019 personal data have raised great attention. Despite that recent regulations force companies to offer choices for each user to opt-in or opt-out of data disclosure, real-world applications usually only provide an \u201call or nothing\u201d binary option for users to either disclose all their data or preserve all data with the cost of no personalized service.<\/jats:p>\n          <jats:p>In this article, we argue that such a binary mechanism is not optimal for both consumers and platforms. To study how different privacy mechanisms affect users\u2019 decisions on information disclosure and how users\u2019 decisions affect the platform\u2019s revenue, we propose a privacy-aware recommendation framework that gives users fine control over their data. In this new framework, users can proactively control which data to disclose based on the tradeoff between anticipated privacy risks and potential utilities. Then we study the impact of different data disclosure mechanisms via simulation with reinforcement learning due to the high cost of real-world experiments. The results show that the platform mechanisms with finer split granularity and more unrestrained disclosure strategy can bring better results for both consumers and platforms than the \u201call or nothing\u201d mechanism adopted by most real-world applications.<\/jats:p>","DOI":"10.1145\/3569452","type":"journal-article","created":{"date-parts":[[2022,10,25]],"date-time":"2022-10-25T13:25:59Z","timestamp":1666704359000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Studying the Impact of Data Disclosure Mechanism in Recommender Systems via Simulation"],"prefix":"10.1145","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2514-6906","authenticated-orcid":false,"given":"Ziqian","family":"Chen","sequence":"first","affiliation":[{"name":"Alibaba Group, Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6146-148X","authenticated-orcid":false,"given":"Fei","family":"Sun","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0325-145X","authenticated-orcid":false,"given":"Yifan","family":"Tang","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5485-2984","authenticated-orcid":false,"given":"Haokun","family":"Chen","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2094-3554","authenticated-orcid":false,"given":"Jinyang","family":"Gao","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1535-9692","authenticated-orcid":false,"given":"Bolin","family":"Ding","sequence":"additional","affiliation":[{"name":"Alibaba Group, Seattle, WA, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,2,7]]},"reference":[{"issue":"4","key":"e_1_3_2_2_2","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MITS.2020.2990189","article-title":"A cooperative multiagent system for traffic signal control using game theory and reinforcement learning","volume":"13","author":"Abdoos Monireh","year":"2020","unstructured":"Monireh Abdoos. 2020. 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