{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T05:22:27Z","timestamp":1768281747230,"version":"3.49.0"},"reference-count":53,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"Macao Polytechnic University research","award":["Project RP\/FCA-05\/2023 (submission code:fca.9098.d329.6)"],"award-info":[{"award-number":["Project RP\/FCA-05\/2023 (submission code:fca.9098.d329.6)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2025.3645352","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T18:39:33Z","timestamp":1767638373000},"page":"3852-3896","source":"Crossref","is-referenced-by-count":0,"title":["Robust Sentiment and Semantic Analysis of Small and Medium-Sized News Headline Datasets: A Study on Sports, Science, and Agricultural Domains"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2879-5521","authenticated-orcid":false,"given":"Zijun","family":"Liang","sequence":"first","affiliation":[{"name":"Faculty of Applied Sciences, Macao Polytechnic University, Macau, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengyu","family":"Lai","sequence":"additional","affiliation":[{"name":"Institution of Collaborative Innovation, University of Macau, Macau, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanpeng","family":"Su","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences, Macao Polytechnic University, Macau, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rouying","family":"Wu","sequence":"additional","affiliation":[{"name":"Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8104-7887","authenticated-orcid":false,"given":"Su-Kit","family":"Tang","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences, Macao Polytechnic University, Macau, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6242-164X","authenticated-orcid":false,"given":"Dennis","family":"Wong","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences, Macao Polytechnic University, Macau, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-17769-6"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/computers8010004"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/app13074550"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10144-1"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107134"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3663363"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3605943"},{"key":"ref9","article-title":"AMMUS: A survey of transformer-based pretrained models in natural language processing","author":"Subramanyam Kalyan","year":"2021","journal-title":"arXiv:2108.05542"},{"key":"ref10","first-page":"7844","article-title":"GPTEval: A survey on assessments of ChatGPT and GPT-4","volume-title":"Proc. Joint Int. Conf. Comput. Linguistics, Lang. Resour. Eval. (LREC-COLING)","author":"Mao"},{"key":"ref11","article-title":"Gpt-4: A review on advancements and opportunities in natural language processing","author":"Ahmad Baktash","year":"2023","journal-title":"arXiv:2305.03195"},{"key":"ref12","article-title":"GPT-4 technical report","volume-title":"arXiv:2303.08774","author":"Achiam","year":"2023"},{"key":"ref13","article-title":"Analyzing sentiment polarity reduction in news presentation through contextual perturbation and large language models","author":"Kuila","year":"2024","journal-title":"arXiv:2402.02145"},{"key":"ref14","first-page":"5944","article-title":"Enhancing emotion prediction in news headlines: Insights from ChatGPT and Seq2Seq models for free-text generation","volume-title":"Proc. Joint Int. Conf. Comput. Linguistics","author":"Gao"},{"key":"ref15","article-title":"Qwen2-audio technical report","volume-title":"arXiv:2407.10759","author":"Chu","year":"2024"},{"key":"ref16","article-title":"Qwen2-VL: Enhancing vision-language model\u2019s perception of the world at any resolution","author":"Wang","year":"2024","journal-title":"arXiv:2409.12191"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3390\/jmse11020407"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2021.3055948"},{"key":"ref19","first-page":"677","article-title":"A study of sentence similarity based on the allminilm- l6-v2 model with \u2018same semantics, different structure\u2019 after fine tuning","volume-title":"Proc. 2nd Int. Conf. Image Algorithms Artif. Intell.","author":"Chen"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.5121\/csit.2023.131923"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.datak.2022.102110"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/SmartNets58706.2023.10215867"},{"key":"ref23","article-title":"The llama 3 herd of models","author":"Grattafiori","year":"2024","journal-title":"arXiv:2407.21783"},{"key":"ref24","article-title":"BERTopic: Neural topic modeling with a class-based TF-IDF procedure","author":"Grootendorst","year":"2022","journal-title":"arXiv:2203.05794"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/2171\/1\/012021"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.11591\/eei.v10i5.3157"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.48161\/qaj.v1n2a50"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120443"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3189996"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3563301"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.372"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-37940-6_17"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108649"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.33395\/sinkron.v8i4.13048"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87334-9_21"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/INTCEC61833.2024.10603240"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.dajour.2022.100071"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.00520"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2021.09.066"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106993"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph18168530"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-024-00973-y"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2021.104484"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-020-05297-6"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbad002"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2020.107312"},{"key":"ref47","article-title":"Is GPT-3 a good data annotator?","author":"Ding","year":"2022","journal-title":"arXiv:2212.10450"},{"key":"ref48","article-title":"Prompting GPT-3 to be reliable","author":"Si","year":"2022","journal-title":"arXiv:2210.09150"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.30871\/jaic.v7i1.4947"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.56578\/ijkis010202"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.56578\/esm010204"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2024.3384333"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2025.105264"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11328992.pdf?arnumber=11328992","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T22:03:06Z","timestamp":1768255386000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11328992\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3645352","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}