{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T00:39:59Z","timestamp":1780447199819,"version":"3.54.1"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput. Soc. Syst."],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1109\/tcss.2022.3143768","type":"journal-article","created":{"date-parts":[[2022,2,17]],"date-time":"2022-02-17T20:24:33Z","timestamp":1645129473000},"page":"1140-1149","source":"Crossref","is-referenced-by-count":14,"title":["Performance Comparison of Transformer-Based Models on Twitter Health Mention Classification"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1805-335X","authenticated-orcid":false,"given":"Pervaiz Iqbal","family":"Khan","sequence":"first","affiliation":[{"name":"German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3930-6600","authenticated-orcid":false,"given":"Imran","family":"Razzak","sequence":"additional","affiliation":[{"name":"School of Information Technology, Deakin University, Geelong, VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6100-8255","authenticated-orcid":false,"given":"Andreas","family":"Dengel","sequence":"additional","affiliation":[{"name":"German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheraz","family":"Ahmed","sequence":"additional","affiliation":[{"name":"German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W19-4302"},{"key":"ref35","article-title":"Mixing Adam and SGD: A combined optimization method","author":"landro","year":"2020","journal-title":"arXiv 2011 08042"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3293883.3295710"},{"key":"ref34","first-page":"9","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"radford","year":"2019","journal-title":"OpenAIRE blog"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1179"},{"key":"ref37","author":"pierse","year":"2021","journal-title":"Transformers interpret"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1112"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/DSAA.2018.00018"},{"key":"ref31","article-title":"BERTweet: A pre-trained language model for English tweets","author":"quoc nguyen","year":"2020","journal-title":"arXiv 2005 10200"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W18-5446"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32381-3_16"},{"key":"ref33","article-title":"ELECTRA: Pre-training text encoders as discriminators rather than generators","author":"clark","year":"2020","journal-title":"arXiv 2003 10555"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6638947"},{"key":"ref32","article-title":"DeBERTa: Decoding-enhanced BERT with disentangled attention","author":"he","year":"2020","journal-title":"arXiv 2006 03654"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2675133.2675218"},{"key":"ref1","year":"2021","journal-title":"Epidemic intelligence - systematic event detection"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref16","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","author":"mikolov","year":"2013","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1017"},{"key":"ref18","first-page":"2200","article-title":"Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining","volume":"10","author":"baccianella","year":"2010","journal-title":"Proc LREC"},{"key":"ref24","first-page":"43","article-title":"Investigating opinion mining through language varieties: A case study of Brazilian and European portuguese tweets","author":"vit\u00f3rio","year":"2017","journal-title":"Anais do X Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana"},{"key":"ref23","article-title":"Building a sentiment corpus of tweets in Brazilian Portuguese","author":"brum","year":"2017","journal-title":"arXiv 1712 08917"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btz682"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1108\/IMDS-12-2017-0582"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1031"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3412841.3441960"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3465336.3475100"},{"key":"ref28","article-title":"ALBERT: A lite BERT for self-supervised learning of language representations","author":"lan","year":"2019","journal-title":"arXiv 1909 11942"},{"key":"ref27","first-page":"5754","article-title":"XLNet: Generalized autoregressive pretraining for language understanding","author":"yang","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref29","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","author":"liu","year":"2019","journal-title":"arXiv 1907 11692"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1202"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380198"},{"key":"ref9","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018","journal-title":"arXiv 1810 04805"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-018-2198-y"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1108"},{"key":"ref5","first-page":"137","article-title":"Did you really just have a heart attack? Towards robust detection of personal health mentions in social media","author":"karisani","year":"2018","journal-title":"Proc World Wide Web Conf"}],"container-title":["IEEE Transactions on Computational Social Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6570650\/10132891\/09715257.pdf?arnumber=9715257","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T18:21:32Z","timestamp":1686594092000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9715257\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6]]},"references-count":37,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tcss.2022.3143768","relation":{},"ISSN":["2329-924X","2373-7476"],"issn-type":[{"value":"2329-924X","type":"electronic"},{"value":"2373-7476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6]]}}}