{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T12:04:41Z","timestamp":1779537881975,"version":"3.53.1"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T00:00:00Z","timestamp":1779667200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Bundesministerium f\u00fcr Wirtschaft und Energie","award":["KK5438302LJ4"],"award-info":[{"award-number":["KK5438302LJ4"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,5,26]]},"DOI":"10.1145\/3795513.3810452","type":"proceedings-article","created":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T11:16:01Z","timestamp":1779534961000},"page":"110-116","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0581-0662","authenticated-orcid":false,"given":"Valentin","family":"Grimm","sequence":"first","affiliation":[{"name":"Computer Science & Automation, TH OWL University of Applied Sciences and Arts, H\u00f6xter, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0107-299X","authenticated-orcid":false,"given":"Eelco","family":"Herder","sequence":"additional","affiliation":[{"name":"Utrecht University, Utrecht, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0937-3551","authenticated-orcid":false,"given":"Jessica","family":"Rubart","sequence":"additional","affiliation":[{"name":"Computer Science & Automation, TH OWL University of Applied Sciences and Arts, H\u00f6xter, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9383-333X","authenticated-orcid":false,"given":"Carsten","family":"R\u00f6cker","sequence":"additional","affiliation":[{"name":"Computer Science & Automation, TH OWL University of Applied Sciences and Arts, Lemgo, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,5,25]]},"reference":[{"key":"e_1_3_3_2_2_2","doi-asserted-by":"publisher","unstructured":"Lamia Alam and Shane Mueller. 2021. Examining the effect of explanation on satisfaction and trust in AI diagnostic systems. BMC Medical Informatics and Decision Making 21 1 (2021) 178. 10.1186\/s12911-021-01542-6","DOI":"10.1186\/s12911-021-01542-6"},{"key":"e_1_3_3_2_3_2","doi-asserted-by":"publisher","unstructured":"Zana Bu\u00e7inca Maja\u00a0Barbara Malaya and Krzysztof\u00a0Z. Gajos. 2021. To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making. Proceedings of the ACM on Human-Computer Interaction 5 CSCW1 (April 2021) 1\u201321. 10.1145\/3449287","DOI":"10.1145\/3449287"},{"key":"e_1_3_3_2_4_2","doi-asserted-by":"publisher","unstructured":"Anshika Choudhary and Anuja Arora. 2021. Linguistic feature based learning model for fake news detection and classification. Expert Systems with Applications 169 (May 2021) 114171. 10.1016\/j.eswa.2020.114171","DOI":"10.1016\/j.eswa.2020.114171"},{"key":"e_1_3_3_2_5_2","doi-asserted-by":"publisher","unstructured":"Melissa DeJonckheere and Lisa\u00a0M Vaughn. 2019. Semistructured interviewing in primary care research: a balance of relationship and rigour. Family Medicine and Community Health 7 2 (March 2019) e000057. 10.1136\/fmch-2018-000057","DOI":"10.1136\/fmch-2018-000057"},{"key":"e_1_3_3_2_6_2","doi-asserted-by":"publisher","unstructured":"Andr\u00e9s Dom\u00ednguez\u00a0Hern\u00e1ndez Richard Owen Dan\u00a0Saattrup Nielsen and Ryan McConville. 2023. Ethical political and epistemic implications of machine learning (mis)information classification: insights from an interdisciplinary collaboration between social and data scientists. Journal of Responsible Innovation 10 1 (Jan. 2023) 1\u201325. 10.1080\/23299460.2023.2222514","DOI":"10.1080\/23299460.2023.2222514"},{"key":"e_1_3_3_2_7_2","doi-asserted-by":"crossref","unstructured":"Jingcheng Du Sharice Preston Hanxiao Sun Ross Shegog Rachel Cunningham Julie Boom Lara Savas Muhammad Amith and Cui Tao. 2021. Using machine learning\u2013based approaches for the detection and classification of human papillomavirus vaccine misinformation: Infodemiology study of reddit discussions. Journal of Medical Internet Research 23 8 (2021) e26478.","DOI":"10.2196\/26478"},{"key":"e_1_3_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3748699.3749798"},{"key":"e_1_3_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/3679058.3688631"},{"key":"e_1_3_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0166-4115(08)62386-9"},{"key":"e_1_3_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/3708359.3712133"},{"key":"e_1_3_3_2_12_2","unstructured":"Lukas-Valentin Herm. 2023. Impact Of Explainable AI On Cognitive Load: Insights From An Empirical Study. arxiv:https:\/\/arXiv.org\/abs\/2304.08861\u00a0[cs.AI] https:\/\/arxiv.org\/abs\/2304.08861"},{"key":"e_1_3_3_2_13_2","doi-asserted-by":"publisher","unstructured":"Andreas Holzinger Andr\u00e9 Carrington and Heimo M\u00fcller. 2020. Measuring the Quality of Explanations: The System Causability Scale (SCS): Comparing Human and Machine Explanations. KI - K\u00fcnstliche Intelligenz 34 2 (june 2020) 193\u2013198. 10.1007\/s13218-020-00636-z","DOI":"10.1007\/s13218-020-00636-z"},{"key":"e_1_3_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-96074-6_2"},{"key":"e_1_3_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-2266-2_11"},{"key":"e_1_3_3_2_16_2","doi-asserted-by":"publisher","unstructured":"Rhema Linder Sina Mohseni Fan Yang Shiva\u00a0K. Pentyala Eric\u00a0D. Ragan and Xia\u00a0Ben Hu. 2021. How level of explanation detail affects human performance in interpretable intelligent systems: A study on explainable fact checking. Applied AI Letters 2 4 (2021) e49. arXiv:https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/ail2.4910.1002\/ail2.49","DOI":"10.1002\/ail2.49"},{"key":"e_1_3_3_2_17_2","volume-title":"Advances in Neural Information Processing Systems","author":"Lundberg Scott\u00a0M","year":"2017","unstructured":"Scott\u00a0M Lundberg and Su-In Lee. 2017. A Unified Approach to Interpreting Model Predictions. In Advances in Neural Information Processing Systems , I.\u00a0Guyon, U.\u00a0Von Luxburg, S.\u00a0Bengio, H.\u00a0Wallach, R.\u00a0Fergus, S.\u00a0Vishwanathan, and R.\u00a0Garnett (Eds.), Vol.\u00a030. Curran Associates, Inc., New York, USA. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2017\/file\/8a20a8621978632d76c43dfd28b67767-Paper.pdf"},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"crossref","unstructured":"Christian Meske and Enrico Bunde. 2023. Design principles for user interfaces in AI-Based decision support systems: The case of explainable hate speech detection. Information Systems Frontiers 25 2 (2023) 743\u2013773.","DOI":"10.1007\/s10796-021-10234-5"},{"key":"e_1_3_3_2_19_2","doi-asserted-by":"crossref","unstructured":"Ingrid Nunes and Dietmar Jannach. 2017. A systematic review and taxonomy of explanations in decision support and recommender systems. User Modeling and User-Adapted Interaction 27 3 (2017) 393\u2013444.","DOI":"10.1007\/s11257-017-9195-0"},{"key":"e_1_3_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/3699682.3728349"},{"key":"e_1_3_3_2_21_2","doi-asserted-by":"crossref","unstructured":"Tahereh Saheb Mouwafac Sidaoui and Bill Schmarzo. 2024. Convergence of artificial intelligence with social media: A bibliometric & qualitative analysis. Telematics and Informatics Reports 14 (2024) 100146.","DOI":"10.1016\/j.teler.2024.100146"},{"key":"e_1_3_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/3514094.3534128"},{"key":"e_1_3_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/B978-155860915-0\/50046-9"},{"key":"e_1_3_3_2_24_2","doi-asserted-by":"publisher","unstructured":"Dylan Slack Satyapriya Krishna Himabindu Lakkaraju and Sameer Singh. 2023. Explaining machine learning models with interactive natural language conversations using TalkToModel. Nature Machine Intelligence 5 8 (july 2023) 873\u2013883. 10.1038\/s42256-023-00692-8","DOI":"10.1038\/s42256-023-00692-8"},{"key":"e_1_3_3_2_25_2","unstructured":"Kacper Sokol and Peter\u00a0A Flach. 2019. Counterfactual Explanations of Machine Learning Predictions: Opportunities and Challenges for AI Safety. SafeAI@ AAAI 2301 (2019) 1\u20134."},{"key":"e_1_3_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/3301275.3302322"},{"key":"e_1_3_3_2_27_2","doi-asserted-by":"publisher","unstructured":"Ashley Suh Kenneth Alperin Harry Li and Steven\u00a0R Gomez. 2025. Don\u2019t Just Translate Agitate: Using Large Language Models as Devil\u2019s Advocates for AI Explanations. 10.5281\/ZENODO.15170455","DOI":"10.5281\/ZENODO.15170455"},{"key":"e_1_3_3_2_28_2","unstructured":"J\u00f6rg\u00a0Schl\u00f6tterer Van Bach\u00a0Nguyen and Christin Seifert. 2024. Xagent: A conversational XAI agent harnessing the power of large language models. 273\u2013280\u00a0pages."},{"key":"e_1_3_3_2_29_2","doi-asserted-by":"publisher","unstructured":"Sebe Vanbrabant Gilles Eerlings Gustavo\u00a0Alberto Rovelo\u00a0Ruiz and Davy Vanacken. 2025. ECHO: Enhancing Conversational Explainable AI through Tool-Augmented Language Models. Proceedings of the ACM on Human-Computer Interaction 9 4 (june 2025) 1\u201333. 10.1145\/3734191","DOI":"10.1145\/3734191"},{"key":"e_1_3_3_2_30_2","doi-asserted-by":"crossref","unstructured":"Rosa Vicari and Nadejda Komendatova. 2023. Systematic meta-analysis of research on AI tools to deal with misinformation on social media during natural and anthropogenic hazards and disasters. Humanities and Social Sciences Communications 10 1 (2023) 1\u201314.","DOI":"10.1057\/s41599-023-01838-0"},{"key":"e_1_3_3_2_31_2","doi-asserted-by":"publisher","unstructured":"Danke Wu Zhenhua Tan Haoran Zhao Taotao Jiang and Ning Geng. 2024. Domain- and category-style clustering for general fake news detection via contrastive learning. Information Processing & Management 61 4 (july 2024) 103725. 10.1016\/j.ipm.2024.103725","DOI":"10.1016\/j.ipm.2024.103725"},{"key":"e_1_3_3_2_32_2","doi-asserted-by":"publisher","unstructured":"Cheng Xu and M-Tahar Kechadi. 2024. An Enhanced Fake News Detection System With Fuzzy Deep Learning. IEEE Access 12 (2024) 88006\u201388021. 10.1109\/ACCESS.2024.3418340","DOI":"10.1109\/ACCESS.2024.3418340"}],"event":{"name":"WebSci Companion '26: 18th ACM Web Science Conference","location":"Braunschweig , Germany","acronym":"WebSci Companion '26","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Companion Publication of the 2026 18th ACM Web Science Conference"],"original-title":[],"deposited":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T11:16:32Z","timestamp":1779534992000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3795513.3810452"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,25]]},"references-count":31,"alternative-id":["10.1145\/3795513.3810452","10.1145\/3795513"],"URL":"https:\/\/doi.org\/10.1145\/3795513.3810452","relation":{},"subject":[],"published":{"date-parts":[[2026,5,25]]},"assertion":[{"value":"2026-05-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}