{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T02:24:25Z","timestamp":1777343065109,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":50,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100007297","name":"Office of Naval Research","doi-asserted-by":"publisher","award":["N000141812108, N00014-17-1-2605"],"award-info":[{"award-number":["N000141812108, N00014-17-1-2605"]}],"id":[{"id":"10.13039\/100007297","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1614576, 1742702, 1820609, 1915801"],"award-info":[{"award-number":["1614576, 1742702, 1820609, 1915801"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330935","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"395-405","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":472,"title":["dEFEND"],"prefix":"10.1145","author":[{"given":"Kai","family":"Shu","sequence":"first","affiliation":[{"name":"Arizona State University, Tempe, AZ, USA"}]},{"given":"Limeng","family":"Cui","sequence":"additional","affiliation":[{"name":"Penn State University, University Park, PA, USA"}]},{"given":"Suhang","family":"Wang","sequence":"additional","affiliation":[{"name":"Penn State University, University Park, PA, USA"}]},{"given":"Dongwon","family":"Lee","sequence":"additional","affiliation":[{"name":"Penn State University, University Park, PA, USA"}]},{"given":"Huan","family":"Liu","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, AZ, USA"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_3_2_1_2_1","volume-title":"Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473","author":"Bahdanau Dzmitry","year":"2014"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963500"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Huimin Chen Maosong Sun Cunchao Tu Yankai Lin and Zhiyuan Liu. 2016. Neural sentiment classification with user and product attention. In EMNLP .  Huimin Chen Maosong Sun Cunchao Tu Yankai Lin and Zhiyuan Liu. 2016. Neural sentiment classification with user and product attention. In EMNLP .","DOI":"10.18653\/v1\/D16-1171"},{"key":"e_1_3_2_1_5_1","volume-title":"Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio.","author":"Cho Kyunghyun","year":"2014"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0128193"},{"key":"e_1_3_2_1_7_1","volume-title":"Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608","author":"Doshi-Velez Finale","year":"2017"},{"key":"e_1_3_2_1_8_1","volume-title":"Techniques for Interpretable Machine Learning. arXiv preprint arXiv:1808.00033","author":"Du Mengnan","year":"2018"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220099"},{"key":"e_1_3_2_1_10_1","unstructured":"Song Feng Ritwik Banerjee and Yejin Choi. 2012. Syntactic stylometry for deception detection. In ACL .   Song Feng Ritwik Banerjee and Yejin Choi. 2012. Syntactic stylometry for deception detection. In ACL ."},{"key":"e_1_3_2_1_11_1","unstructured":"Gisel Bastidas Guacho Sara Abdali Neil Shah and Evangelos E Papalexakis. 2018. Semi-supervised Content-based Detection of Misinformation via Tensor Embeddings. In ASONAM .  Gisel Bastidas Guacho Sara Abdali Neil Shah and Evangelos E Papalexakis. 2018. Semi-supervised Content-based Detection of Misinformation via Tensor Embeddings. In ASONAM ."},{"key":"e_1_3_2_1_12_1","volume-title":"Exploiting Emotions for Fake News Detection on Social Media. arXiv preprint arXiv:1903.01728","author":"Guo Chuan","year":"2019"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271709"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098131"},{"key":"e_1_3_2_1_15_1","unstructured":"Seyedmehdi Hosseinimotlagh and Evangelos E Papalexakis. 2018. Unsupervised Content-Based Identification of Fake News Articles with Tensor Decomposition Ensembles. (2018).  Seyedmehdi Hosseinimotlagh and Evangelos E Papalexakis. 2018. Unsupervised Content-Based Identification of Fake News Articles with Tensor Decomposition Ensembles. (2018)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_3_2_1_17_1","unstructured":"Yangfeng Ji and Jacob Eisenstein. 2014. Representation learning for text-level discourse parsing. In ACL .  Yangfeng Ji and Jacob Eisenstein. 2014. Representation learning for text-level discourse parsing. In ACL ."},{"key":"e_1_3_2_1_18_1","unstructured":"Zhiwei Jin Juan Cao Yongdong Zhang and Jiebo Luo. 2016. News Verification by Exploiting Conflicting Social Viewpoints in Microblogs.. In AAAI .   Zhiwei Jin Juan Cao Yongdong Zhang and Jiebo Luo. 2016. News Verification by Exploiting Conflicting Social Viewpoints in Microblogs.. In AAAI ."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2617078"},{"key":"e_1_3_2_1_20_1","unstructured":"Hamid Karimi Proteek Roy Sari Saba-Sadiya and Jiliang Tang. 2018. Multi-Source Multi-Class Fake News Detection. In COLING .  Hamid Karimi Proteek Roy Sari Saba-Sadiya and Jiliang Tang. 2018. Multi-Source Multi-Class Fake News Detection. In COLING ."},{"key":"e_1_3_2_1_21_1","volume-title":"Learning Hierarchical Discourse-level Structure for Fake News Detection. arXiv preprint arXiv:1903.07389","author":"Karimi Hamid","year":"2019"},{"key":"e_1_3_2_1_22_1","volume-title":"Visualizing and understanding recurrent networks. arXiv preprint arXiv:1506.02078","author":"Karpathy Andrej","year":"2015"},{"key":"e_1_3_2_1_23_1","volume-title":"Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882","author":"Kim Yoon","year":"2014"},{"key":"e_1_3_2_1_24_1","volume-title":"Understanding black-box predictions via influence functions. arXiv preprint arXiv:1703.04730","author":"Koh Pang Wei","year":"2017"},{"key":"e_1_3_2_1_25_1","volume-title":"International Conference on Machine Learning. 1188--1196","author":"Le Quoc","year":"2014"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290960"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220001"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220027"},{"key":"e_1_3_2_1_29_1","unstructured":"Jiasen Lu Jianwei Yang Dhruv Batra and Devi Parikh. 2016. Hierarchical question-image co-attention for visual question answering. In NIPS .   Jiasen Lu Jianwei Yang Dhruv Batra and Devi Parikh. 2016. Hierarchical question-image co-attention for visual question answering. In NIPS ."},{"key":"e_1_3_2_1_30_1","volume-title":"Fake News Detection on Social Media using Geometric Deep Learning. arXiv preprint arXiv:1902.06673","author":"Monti Federico","year":"2019"},{"key":"e_1_3_2_1_31_1","volume-title":"et almbox","author":"Pedregosa Fabian","year":"2011"},{"key":"e_1_3_2_1_33_1","volume-title":"Deep contextualized word representations. arXiv preprint arXiv:1802.05365","author":"Peters Matthew E","year":"2018"},{"key":"e_1_3_2_1_34_1","volume-title":"A Stylometric Inquiry into Hyperpartisan and Fake News. arXiv preprint arXiv:1702.05638","author":"Potthast Martin","year":"2017"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"crossref","unstructured":"Feng Qian Chengyue Gong Karishma Sharma and Yan Liu. 2018. Neural User Response Generator: Fake News Detection with Collective User Intelligence.. In IJCAI .   Feng Qian Chengyue Gong Karishma Sharma and Yan Liu. 2018. Neural User Response Generator: Fake News Detection with Collective User Intelligence.. In IJCAI .","DOI":"10.24963\/ijcai.2018\/533"},{"key":"e_1_3_2_1_36_1","volume-title":"Hawaii International Conference on System Sciences .","author":"Rubin Victoria L","year":"2015"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132877"},{"key":"e_1_3_2_1_38_1","volume-title":"FakeNewsNet: A Data Repository with News Content, Social Context and Dynamic Information for Studying Fake News on Social Media. arXiv preprint arXiv:1809.01286","author":"Shu Kai","year":"2018"},{"key":"e_1_3_2_1_39_1","volume-title":"2019 a. Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation. arXiv preprint arXiv:1903.09196","author":"Shu Kai","year":"2019"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3137597.3137600"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"crossref","unstructured":"Kai Shu Suhang Wang and Huan Liu. 2019 b. Beyond News Contents: The Role of Social Context for Fake News Detection. (2019).  Kai Shu Suhang Wang and Huan Liu. 2019 b. Beyond News Contents: The Role of Social Context for Fake News Detection. (2019).","DOI":"10.1145\/3341161.3342927"},{"key":"e_1_3_2_1_42_1","volume-title":"The Role of User Profile for Fake News Detection. arXiv preprint arXiv:1904.13355","author":"Shu Kai","year":"2018"},{"key":"e_1_3_2_1_43_1","volume-title":"Stefano Moret, and Luca de Alfaro.","author":"Tacchini Eugenio","year":"2017"},{"key":"e_1_3_2_1_44_1","volume-title":"Liar Pants on Fire\": A New Benchmark Dataset for Fake News Detection. arXiv preprint arXiv:1705.00648","author":"Wang William Yang","year":"2017"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219903"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159677"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"crossref","unstructured":"Fan Yang Ninghao Liu Suhang Wang and Xia Hu. 2018. Towards Interpretation of Recommender Systems with Sorted Explanation Paths. In ICDM .  Fan Yang Ninghao Liu Suhang Wang and Xia Hu. 2018. Towards Interpretation of Recommender Systems with Sorted Explanation Paths. In ICDM .","DOI":"10.1109\/ICDM.2018.00082"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Fan Yang Shiva K Pentyala Sina Mohseni Mengnan Du Hao Yuan Rhema Linder Eric D Ragan Shuiwang Ji and Xia Ben Hu. 2019 a. XFake: Explainable Fake News Detector with Visualizations. (2019).  Fan Yang Shiva K Pentyala Sina Mohseni Mengnan Du Hao Yuan Rhema Linder Eric D Ragan Shuiwang Ji and Xia Ben Hu. 2019 a. XFake: Explainable Fake News Detector with Visualizations. (2019).","DOI":"10.1145\/3308558.3314119"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"crossref","unstructured":"Shuo Yang Kai Shu Suhang Wang Renjie Gu Fan Wu and Huan Liu. 2019 b. Unsupervised Fake News Detection on Social Media: A Generative Approach. In AAAI .  Shuo Yang Kai Shu Suhang Wang Renjie Gu Fan Wu and Huan Liu. 2019 b. Unsupervised Fake News Detection on Social Media: A Generative Approach. In AAAI .","DOI":"10.1609\/aaai.v33i01.33015644"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","unstructured":"Zichao Yang Diyi Yang Chris Dyer Xiaodong He Alex Smola and Eduard Hovy. 2016. Hierarchical attention networks for document classification. In NAACL .  Zichao Yang Diyi Yang Chris Dyer Xiaodong He Alex Smola and Eduard Hovy. 2016. Hierarchical attention networks for document classification. In NAACL .","DOI":"10.18653\/v1\/N16-1174"},{"key":"e_1_3_2_1_51_1","volume-title":"Fake News: A Survey of Research, Detection Methods, and Opportunities. arXiv preprint arXiv:1812.00315","author":"Zhou Xinyi","year":"2018"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3291382"}],"event":{"name":"KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Anchorage AK USA","acronym":"KDD '19","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330935","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330935","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330935","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:26:03Z","timestamp":1750206363000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330935"}},"subtitle":["Explainable Fake News Detection"],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":50,"alternative-id":["10.1145\/3292500.3330935","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330935","relation":{},"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"2019-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}