{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T17:02:27Z","timestamp":1776186147720,"version":"3.50.1"},"reference-count":50,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing & Management"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ipm.2026.104805","type":"journal-article","created":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T21:44:59Z","timestamp":1775598299000},"page":"104805","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["DiaCOLQ: A benchmark for Chinese offensive language quadruple prediction in multi-turn dialogues"],"prefix":"10.1016","volume":"63","author":[{"given":"Yifan","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziyi","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Litian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahao","family":"Bai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junyu","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bohan","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fanliang","family":"Bu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.ipm.2026.104805_b1","series-title":"Llama 3 model card","author":"AI@Meta","year":"2024"},{"issue":"3","key":"10.1016\/j.ipm.2026.104805_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2023.103270","article-title":"ISE-hate: A benchmark corpus for inter-faith, sectarian, and ethnic hatred detection on social media in Urdu","volume":"60","author":"Akram","year":"2023","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104805_b3","series-title":"Claude 3.5 sonnet","author":"Anthropic","year":"2024"},{"key":"10.1016\/j.ipm.2026.104805_b4","series-title":"Findings of the association for computational linguistics: ACL 2025","first-page":"10206","article-title":"STATE ToxiCN: A benchmark for span-level target-aware toxicity extraction in Chinese hate speech detection","author":"Bai","year":"2025"},{"key":"10.1016\/j.ipm.2026.104805_b5","series-title":"Proceedings of the 59th annual meeting of the association for computational linguistics and the 11th international joint conference on natural language processing (volume 1: long papers)","first-page":"340","article-title":"Aspect-category-opinion-sentiment quadruple extraction with implicit aspects and opinions","author":"Cai","year":"2021"},{"key":"10.1016\/j.ipm.2026.104805_b6","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.chb.2018.12.029","article-title":"Understanding emotions in text using deep learning and big data","volume":"93","author":"Chatterjee","year":"2019","journal-title":"Computers in Human Behavior"},{"issue":"1","key":"10.1016\/j.ipm.2026.104805_b7","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1002\/pra2.811","article-title":"The causality between offensive language use and negative emotions in the public event\u2014An empirical study using convergent cross mapping","volume":"60","author":"Chen","year":"2023","journal-title":"Proceedings of the Association for Information Science and Technology"},{"key":"10.1016\/j.ipm.2026.104805_b8","doi-asserted-by":"crossref","unstructured":"Davidson, T., Warmsley, D., Macy, M., & Weber, I. (2017). Automated hate speech detection and the problem of offensive language. vol. 11, In Proceedings of the international AAAI conference on web and social media (pp. 512\u2013515). 1.","DOI":"10.1609\/icwsm.v11i1.14955"},{"key":"10.1016\/j.ipm.2026.104805_b9","doi-asserted-by":"crossref","unstructured":"Deng, J., Zhou, J., Sun, H., Zheng, C., Mi, F., Meng, H., & Huang, M. (2022). COLD: A benchmark for Chinese offensive language detection. In Proceedings of the 2022 conference on empirical methods in natural language processing (pp. 11580\u201311599).","DOI":"10.18653\/v1\/2022.emnlp-main.796"},{"key":"10.1016\/j.ipm.2026.104805_b10","doi-asserted-by":"crossref","unstructured":"ElSherief, M., Ziems, C., Muchlinski, D., Anupindi, V., Seybolt, J., De Choudhury, M., & Yang, D. (2021). Latent hatred: A benchmark for understanding implicit hate speech. In Proceedings of the 2021 conference on empirical methods in natural language processing (pp. 345\u2013363).","DOI":"10.18653\/v1\/2021.emnlp-main.29"},{"issue":"5","key":"10.1016\/j.ipm.2026.104805_b11","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1037\/h0031619","article-title":"Measuring nominal scale agreement among many raters.","volume":"76","author":"Fleiss","year":"1971","journal-title":"Psychological Bulletin"},{"issue":"11","key":"10.1016\/j.ipm.2026.104805_b12","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e32246","article-title":"Analyzing hate speech dynamics on Twitter\/X: Insights from conversational data and the impact of user interaction patterns","volume":"10","author":"Fonseca","year":"2024","journal-title":"Heliyon"},{"key":"10.1016\/j.ipm.2026.104805_b13","doi-asserted-by":"crossref","unstructured":"Founta, A., Djouvas, C., Chatzakou, D., Leontiadis, I., Blackburn, J., Stringhini, G., Vakali, A., Sirivianos, M., & Kourtellis, N. (2018). Large scale crowdsourcing and characterization of twitter abusive behavior. vol. 12, In Proceedings of the international AAAI conference on web and social media. 1.","DOI":"10.1609\/icwsm.v12i1.14991"},{"issue":"3","key":"10.1016\/j.ipm.2026.104805_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104079","article-title":"Exploring hate speech dynamics: The emotional, linguistic, and thematic impact on social media users","volume":"62","author":"Ghenai","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104805_b15","series-title":"Gemini 2.0 flash","author":"Google","year":"2025"},{"key":"10.1016\/j.ipm.2026.104805_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.111039","article-title":"SEEC and CHASE: An emotion-cause pair-oriented approach and conversational dataset with heterogeneous emotions for empathetic response generation","volume":"280","author":"Gupta","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.ipm.2026.104805_b17","series-title":"Is information extraction solved by ChatGPT? An analysis of performance, evaluation criteria, robustness and errors","author":"Han","year":"2023"},{"key":"10.1016\/j.ipm.2026.104805_b18","doi-asserted-by":"crossref","unstructured":"Hartvigsen, T., Gabriel, S., Palangi, H., Sap, M., Ray, D., & Kamar, E. (2022). Toxigen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection. In Proceedings of the 60th annual meeting of the association for computational linguistics (volume 1: long papers) (pp. 3309\u20133326).","DOI":"10.18653\/v1\/2022.acl-long.234"},{"key":"10.1016\/j.ipm.2026.104805_b19","series-title":"Proceedings of the 59th annual meeting of the association for computational linguistics and the 11th international joint conference on natural language processing (volume 1: long papers)","first-page":"7042","article-title":"DialogueCRN: Contextual reasoning networks for emotion recognition in conversations","author":"Hu","year":"2021"},{"key":"10.1016\/j.ipm.2026.104805_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.osnem.2021.100182","article-title":"Swsr: A chinese dataset and lexicon for online sexism detection","volume":"27","author":"Jiang","year":"2022","journal-title":"Online Social Networks and Media"},{"issue":"2, Part B","key":"10.1016\/j.ipm.2026.104805_b21","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104470","article-title":"Developing continuous toxicity detection against increasing types of perturbed toxic text","volume":"63","author":"Kang","year":"2026","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104805_b22","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106458","article-title":"A deep neural network based multi-task learning approach to hate speech detection","volume":"210","author":"Kapil","year":"2020","journal-title":"Knowledge-Based Systems"},{"issue":"23","key":"10.1016\/j.ipm.2026.104805_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e40611","article-title":"Predicting the victims of hate speech on microblogging platforms","volume":"10","author":"Khan","year":"2024","journal-title":"Heliyon"},{"issue":"2","key":"10.1016\/j.ipm.2026.104805_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104309","article-title":"Distilling knowledge from large language models: A concept bottleneck model for hate and counter speech recognition","volume":"63","author":"Labadie-Tamayo","year":"2026","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104805_b25","doi-asserted-by":"crossref","DOI":"10.1016\/j.avb.2020.101453","article-title":"The language of bullying: social issues on Chinese websites","volume":"53","author":"Li","year":"2020","journal-title":"Aggression and Violent Behavior"},{"key":"10.1016\/j.ipm.2026.104805_b26","series-title":"Findings of the association for computational linguistics: ACL 2023","first-page":"13449","article-title":"DiaASQ: A benchmark of conversational aspect-based sentiment quadruple analysis","author":"Li","year":"2023"},{"key":"10.1016\/j.ipm.2026.104805_b27","series-title":"Proceedings of the eighth international joint conference on natural language processing (volume 1: long papers)","first-page":"986","article-title":"Dailydialog: A manually labelled multi-turn dialogue dataset","author":"Li","year":"2017"},{"issue":"5","key":"10.1016\/j.ipm.2026.104805_b28","doi-asserted-by":"crossref","first-page":"2485","DOI":"10.1109\/TKDE.2020.3008563","article-title":"Topic-guided conversational recommender in multiple domains","volume":"34","author":"Liao","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.ipm.2026.104805_b29","series-title":"DeepSeek-V3 technical report","author":"Liu","year":"2025"},{"key":"10.1016\/j.ipm.2026.104805_b30","series-title":"Proceedings of the 61st annual meeting of the association for computational linguistics (volume 1: long papers)","first-page":"16235","article-title":"Facilitating fine-grained detection of Chinese toxic language: Hierarchical taxonomy, resources, and benchmarks","author":"Lu","year":"2023"},{"key":"10.1016\/j.ipm.2026.104805_b31","doi-asserted-by":"crossref","unstructured":"Mathew, B., Saha, P., Yimam, S. M., Biemann, C., Goyal, P., & Mukherjee, A. (2021). Hatexplain: A benchmark dataset for explainable hate speech detection. vol. 35, In Proceedings of the AAAI conference on artificial intelligence (pp. 14867\u201314875). 17.","DOI":"10.1609\/aaai.v35i17.17745"},{"key":"10.1016\/j.ipm.2026.104805_b32","doi-asserted-by":"crossref","DOI":"10.7717\/peerj-cs.1934","article-title":"A survey on multi-lingual offensive language detection","volume":"10","author":"Mnassri","year":"2024","journal-title":"PeerJ Computer Science"},{"issue":"6","key":"10.1016\/j.ipm.2026.104805_b33","doi-asserted-by":"crossref","first-page":"4663","DOI":"10.1007\/s40747-021-00608-2","article-title":"ETHOS: a multi-label hate speech detection dataset","volume":"8","author":"Mollas","year":"2022","journal-title":"Complex & Intelligent Systems"},{"issue":"4","key":"10.1016\/j.ipm.2026.104805_b34","doi-asserted-by":"crossref","first-page":"3055","DOI":"10.1007\/s10462-022-10248-8","article-title":"Recent advances in deep learning based dialogue systems: A systematic survey","volume":"56","author":"Ni","year":"2023","journal-title":"Artificial Intelligence Review"},{"key":"10.1016\/j.ipm.2026.104805_b35","series-title":"Hello gpt-4o","author":"OpenAI","year":"2024"},{"key":"10.1016\/j.ipm.2026.104805_b36","doi-asserted-by":"crossref","unstructured":"Pavlopoulos, J., Sorensen, J., Laugier, L., & Androutsopoulos, I. (2021). SemEval-2021 task 5: Toxic spans detection. In Proceedings of the 15th international workshop on semantic evaluation (pp. 59\u201369).","DOI":"10.18653\/v1\/2021.semeval-1.6"},{"key":"10.1016\/j.ipm.2026.104805_b37","series-title":"Advances in data and information sciences: Proceedings of ICDIS 2019","first-page":"433","article-title":"A review on offensive language detection","author":"Pradhan","year":"2020"},{"key":"10.1016\/j.ipm.2026.104805_b38","unstructured":"Rao, X., Zhang, Y., Jia, Q., Liu, X., Peng, S., et al. (2023). Chinese Hate Speech detection method Based on RoBERTa-WWM. In Proceedings of the 22nd Chinese national conference on computational linguistics (pp. 501\u2013511)."},{"key":"10.1016\/j.ipm.2026.104805_b39","doi-asserted-by":"crossref","unstructured":"Relia, K., Li, Z., Cook, S. H., & Chunara, R. (2019). Race, ethnicity and national origin-based discrimination in social media and hate crimes across 100 US cities. vol. 13, In Proceedings of the international AAAI conference on web and social media (pp. 417\u2013427).","DOI":"10.1609\/icwsm.v13i01.3354"},{"key":"10.1016\/j.ipm.2026.104805_b40","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113619","article-title":"KALD: A knowledge augmented multi-contrastive learning model for low resource abusive language detection","author":"Song","year":"2025","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.ipm.2026.104805_b41","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.neucom.2019.03.087","article-title":"Chinese metaphor sentiment computing via considering culture","volume":"352","author":"Su","year":"2019","journal-title":"Neurocomputing"},{"key":"10.1016\/j.ipm.2026.104805_b42","series-title":"Findings of the association for computational linguistics: ACL 2022","first-page":"3906","article-title":"On the safety of conversational models: Taxonomy, dataset, and benchmark","author":"Sun","year":"2022"},{"key":"10.1016\/j.ipm.2026.104805_b43","series-title":"ChatGLM: A family of large language models from GLM-130B to GLM-4 all tools","author":"Team","year":"2024"},{"key":"10.1016\/j.ipm.2026.104805_b44","series-title":"qwen","author":"Team","year":"2024"},{"key":"10.1016\/j.ipm.2026.104805_b45","series-title":"Proceedings of the NAACL student research workshop","first-page":"88","article-title":"Hateful symbols or hateful people? Predictive features for hate speech detection on Twitter","author":"Waseem","year":"2016"},{"key":"10.1016\/j.ipm.2026.104805_b46","series-title":"Proceedings of the 2024 conference on empirical methods in natural language processing","first-page":"6012","article-title":"ToxiCloakCN: Evaluating robustness of offensive language detection in Chinese with cloaking perturbations","author":"Xiao","year":"2024"},{"key":"10.1016\/j.ipm.2026.104805_b47","series-title":"Proceedings of the 31st international conference on computational linguistics","first-page":"9533","article-title":"SCCD: A session-based dataset for Chinese cyberbullying detection","author":"Yang","year":"2025"},{"key":"10.1016\/j.ipm.2026.104805_b48","series-title":"61st annual meeting of the association for computational linguistics","first-page":"762","article-title":"Target-based offensive language identification","author":"Zampieri","year":"2023"},{"key":"10.1016\/j.ipm.2026.104805_b49","series-title":"Proceedings of the 2021 conference on empirical methods in natural language processing","first-page":"9209","article-title":"Aspect sentiment quad prediction as paraphrase generation","author":"Zhang","year":"2021"},{"key":"10.1016\/j.ipm.2026.104805_b50","series-title":"Findings of the association for computational linguistics: EMNLP 2022","first-page":"3576","article-title":"Towards identifying social bias in dialog systems: Framework, dataset, and benchmark","author":"Zhou","year":"2022"}],"container-title":["Information Processing & Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001962?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001962?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:09:05Z","timestamp":1776182945000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457326001962"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":50,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["S0306457326001962"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104805","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"DiaCOLQ: A benchmark for Chinese offensive language quadruple prediction in multi-turn dialogues","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104805","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104805"}}