{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T13:19:09Z","timestamp":1782220749776,"version":"3.54.5"},"reference-count":70,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T00:00:00Z","timestamp":1674604800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["U21B2026, 62002191"],"award-info":[{"award-number":["U21B2026, 62002191"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Tsinghua University Guoqiang Research Institute"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2023,4,30]]},"abstract":"<jats:p>\n            As recommender systems become increasingly important in daily human decision-making, users are demanding convincing explanations to understand why they get the specific recommendation results. Although a number of explainable recommender systems have recently been proposed, there still lacks an understanding of what users really need in a recommendation explanation. The actual reason behind users\u2019 intention to examine and consume (e.g., click and watch a movie) can be the window to answer this question and is named as\n            <jats:italic>self-explanation<\/jats:italic>\n            in this work. In addition, humans usually make recommendations accompanied by explanations, but there remain fewer studies on how humans explain and what we can learn from human-generated explanations.\n          <\/jats:p>\n          <jats:p>\n            To investigate these questions, we conduct a novel multi-role, multi-session user study in which users interact with multiple types of system-generated explanations as well as human-generated explanations, namely\n            <jats:italic>peer-explanation<\/jats:italic>\n            . During the study, users\u2019 intentions, expectations, and experiences are tracked in several phases, including before and after the users are presented with an explanation and after the content is examined. Through comprehensive investigations, three main findings have been made: First, we observe not only the positive but also the negative effects of explanations, and the impact varies across different types of explanations. Moreover, human-generated explanation,\n            <jats:italic>peer-explanation<\/jats:italic>\n            , performs better in increasing user intentions and helping users to better construct preferences, which results in better user satisfaction. Second, based on users\u2019\n            <jats:italic>self-explanation<\/jats:italic>\n            , the information accuracy is measured and found to be a major factor associated with user satisfaction. Some other factors, such as unfamiliarity and similarity, are also discovered and summarized. Third, through annotations of the information aspects used in the human-generated\n            <jats:italic>self-explanation<\/jats:italic>\n            and\n            <jats:italic>peer-explanation<\/jats:italic>\n            , patterns of how humans explain are investigated, including what information and how much information is utilized. In addition, based on the findings, a human-inspired explanation approach is proposed and found to increase user satisfaction, revealing the potential improvement of further incorporating more human patterns in recommendation explanations.\n          <\/jats:p>\n          <jats:p>These findings have shed light on the deeper understanding of the recommendation explanation and further research on its evaluation and generation. Furthermore, the collected data, including human-generated explanations by both the external peers and the users\u2019 selves, will be released to support future research works on explanation evaluation.<\/jats:p>","DOI":"10.1145\/3565480","type":"journal-article","created":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T15:08:42Z","timestamp":1668697722000},"page":"1-31","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":39,"title":["User Perception of Recommendation Explanation: Are Your Explanations What Users Need?"],"prefix":"10.1145","volume":"41","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-0247-2496","authenticated-orcid":false,"given":"Hongyu","family":"Lu","sequence":"first","affiliation":[{"name":"Tsinghua University &amp; Tencent, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-5604-7527","authenticated-orcid":false,"given":"Weizhi","family":"Ma","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-2933-6363","authenticated-orcid":false,"given":"Yifan","family":"Wang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-3158-1920","authenticated-orcid":false,"given":"Min","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-6148-6329","authenticated-orcid":false,"given":"Xiang","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-0140-4512","authenticated-orcid":false,"given":"Yiqun","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-6097-7807","authenticated-orcid":false,"given":"Tat-Seng","family":"Chua","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-8762-8268","authenticated-orcid":false,"given":"Shaoping","family":"Ma","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,1,25]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109913"},{"key":"e_1_3_2_3_2","doi-asserted-by":"crossref","unstructured":"Krisztian Balog and Filip Radlinski. 2020. Measuring recommendation explanation quality: The conflicting goals of explanations. (2020).","DOI":"10.1145\/3397271.3401032"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3025171.3025209"},{"key":"e_1_3_2_5_2","first-page":"153","volume-title":"Beyond Personalization Workshop, IUI","author":"Bilgic Mustafa","year":"2005","unstructured":"Mustafa Bilgic and Raymond J. Mooney. 2005. Explaining recommendations: Satisfaction vs. promotion. In Beyond Personalization Workshop, IUI, Vol. 5. 153."},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376746"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/2365952.2365964"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959153"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186070"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441762"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/2533670.2533675"},{"key":"e_1_3_2_12_2","article-title":"Measuring \u201cwhy\u201d in recommender systems: A comprehensive survey on the evaluation of explainable recommendation","author":"Chen Xu","year":"2022","unstructured":"Xu Chen, Yongfeng Zhang, and Ji-Rong Wen. 2022. Measuring \u201cwhy\u201d in recommender systems: A comprehensive survey on the evaluation of explainable recommendation. arXiv preprint arXiv:2202.06466 (2022).","journal-title":"arXiv preprint arXiv:2202.06466"},{"key":"e_1_3_2_13_2","unstructured":"IJCAI\u201920 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence Zhongxia Chen Xiting Wang Xing Xie Mehul Parsana Akshay Soni Xiang Ao Enhong Chen Towards explainable conversational recommendation 2021 414"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-008-9051-3"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474274"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3301275.3302274"},{"key":"e_1_3_2_17_2","volume-title":"IUI Workshops","author":"Donkers Tim","year":"2018","unstructured":"Tim Donkers, Benedikt Loepp, and J\u00fcrgen Ziegler. 2018. Explaining recommendations by means of user reviews. In IUI Workshops."},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412778"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/CEC-EEE.2006.14"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v32i3.2365"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013622"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijhcs.2013.12.007"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511937"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462939"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1145\/358916.358995"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/3386392.3399302"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.2307\/25148760"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109915"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1145\/3301275.3302306"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1145\/1454008.1454042"},{"key":"e_1_3_2_32_2","volume-title":"IUI Workshops","author":"Kunkel Johannes","year":"2018","unstructured":"Johannes Kunkel, Tim Donkers, Catalin-Mihai Barbu, and J\u00fcrgen Ziegler. 2018. Trust-related effects of expertise and similarity cues in human-generated recommendations. In IUI Workshops."},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300717"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411992"},{"key":"e_1_3_2_35_2","article-title":"Personalized transformer for explainable recommendation","author":"Li Lei","year":"2021","unstructured":"Lei Li, Yongfeng Zhang, and Li Chen. 2021. Personalized transformer for explainable recommendation. arXiv preprint arXiv:2105.11601 (2021).","journal-title":"arXiv preprint arXiv:2105.11601"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-021-00913-3"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481962"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3142260"},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/3511019"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313607"},{"key":"e_1_3_2_41_2","doi-asserted-by":"publisher","DOI":"10.1145\/2507157.2507163"},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1145\/3301275.3302313"},{"key":"e_1_3_2_43_2","doi-asserted-by":"publisher","DOI":"10.1145\/3320435.3320457"},{"key":"e_1_3_2_44_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-017-9195-0"},{"key":"e_1_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.1145\/1357054.1357222"},{"key":"e_1_3_2_46_2","doi-asserted-by":"publisher","DOI":"10.1609\/hcomp.v2i1.13161"},{"key":"e_1_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-011-0215-0"},{"key":"e_1_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498515"},{"key":"e_1_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.1145\/1111449.1111475"},{"key":"e_1_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-011-9115-7"},{"key":"e_1_3_2_51_2","doi-asserted-by":"publisher","DOI":"10.1145\/502716.502737"},{"key":"e_1_3_2_52_2","doi-asserted-by":"publisher","DOI":"10.1145\/3172944.3173012"},{"key":"e_1_3_2_53_2","doi-asserted-by":"publisher","DOI":"10.1145\/506443.506619"},{"key":"e_1_3_2_54_2","volume-title":"WebKDD Workshop on Web Mining and Web Usage Analysis","author":"Symeonidis Panagiotis","year":"2008","unstructured":"Panagiotis Symeonidis, Alexandros Nanopoulos, and Yannis Manolopoulos. 2008. Justified recommendations based on content and rating data. In WebKDD Workshop on Web Mining and Web Usage Analysis."},{"key":"e_1_3_2_55_2","doi-asserted-by":"publisher","DOI":"10.1145\/1639714.1639777"},{"key":"e_1_3_2_56_2","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462847"},{"key":"e_1_3_2_57_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482420"},{"key":"e_1_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-011-9117-5"},{"key":"e_1_3_2_59_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7637-6_10"},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412230"},{"key":"e_1_3_2_61_2","doi-asserted-by":"publisher","DOI":"10.1145\/1502650.1502661"},{"key":"e_1_3_2_62_2","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330989"},{"key":"e_1_3_2_63_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015329"},{"key":"e_1_3_2_64_2","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474240"},{"key":"e_1_3_2_65_2","doi-asserted-by":"publisher","DOI":"10.1080\/10447318.2017.1357904"},{"key":"e_1_3_2_66_2","article-title":"Explainable recommendation: A survey and new perspectives","author":"Zhang Yongfeng","year":"2018","unstructured":"Yongfeng Zhang and Xu Chen. 2018. Explainable recommendation: A survey and new perspectives. arXiv preprint arXiv:1804.11192 (2018).","journal-title":"arXiv preprint arXiv:1804.11192"},{"key":"e_1_3_2_67_2","doi-asserted-by":"publisher","DOI":"10.1145\/2600428.2609579"},{"key":"e_1_3_2_68_2","unstructured":"Ruijing Zhao Izak Benbasat and Hasan Cavusoglu. 2019. Do users always want to know more? Investigating the relationship between system transparency and users\u2019 trust in advice-giving systems. (2019)."},{"key":"e_1_3_2_69_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531267"},{"key":"e_1_3_2_70_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3146178"},{"key":"e_1_3_2_71_2","article-title":"Faithfully explainable recommendation via neural logic reasoning","volume":"2104","author":"Zhu Yaxin","year":"2021","unstructured":"Yaxin Zhu, Yikun Xian, Zuohui Fu, Gerard de Melo, and Yongfeng Zhang. 2021. Faithfully explainable recommendation via neural logic reasoning. CoRR abs\/2104.07869 (2021). arXiv:2104.07869https:\/\/2.zoppoz.workers.dev:443\/https\/arxiv.org\/abs\/2104.07869.","journal-title":"CoRR"}],"container-title":["ACM Transactions on Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/dl.acm.org\/doi\/10.1145\/3565480","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/dl.acm.org\/doi\/pdf\/10.1145\/3565480","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:48:50Z","timestamp":1750182530000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/dl.acm.org\/doi\/10.1145\/3565480"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,25]]},"references-count":70,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,4,30]]}},"alternative-id":["10.1145\/3565480"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3565480","relation":{},"ISSN":["1046-8188","1558-2868"],"issn-type":[{"value":"1046-8188","type":"print"},{"value":"1558-2868","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,25]]},"assertion":[{"value":"2021-01-14","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-09-06","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-01-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}