{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T11:09:58Z","timestamp":1773486598934,"version":"3.50.1"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T00:00:00Z","timestamp":1773446400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T00:00:00Z","timestamp":1773446400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100006393","name":"Universidad de Granada","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006393","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Evolving Systems"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The process of group decision-making is an integral component not only for quotidian interactions but also for strategic deliberations. However, it is profoundly shaped by the inherent semantic indeterminacy of natural language. This linguistic ambiguity starkly contrasts the syntactic and semantic precision characteristic of machine-generated language. Furthermore, the conveyance of affective states\u2013such as aggressiveness or elation\u2013via natural language introduces a layer of complexity that can significantly perturb the equilibrium of the group decision-making process. In response to these challenges, we propose an advanced consensus-reaching methodology based on sentiment analysis to quantify and mitigate aggressiveness in discourse. This study conducts a comparative evaluation of three state-of-the-art large language models: Gemini, Copilot, and ChatGPT for their efficacy in detecting and assessing hostility. By calibrating the influence of individual participants based on their degree of linguistic aggression, the proposed framework attenuates the disproportionate impact of dominant voices, thus fostering a more balanced and equitable deliberative environment. This methodological innovation not only incentivizes the adoption of a more dispassionate and constructive linguistic register but also safeguards the integrity of collective decision-making processes against the distortive effects of undue emotional influence. Across five repeated evaluations per comment, ChatGPT and Gemini exhibited\n                    <jats:inline-formula>\n                      <jats:tex-math>$$&lt;5\\%$$<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    variance, while Copilot showed\n                    <jats:inline-formula>\n                      <jats:tex-math>$$\\approx 8-12 \\%$$<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    ; in all cases, hostility-aware weighting reduced the most aggressive expert\u2019s influence by\n                    <jats:inline-formula>\n                      <jats:tex-math>$$ \\approx 27-29 \\%$$<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    , yielding robust group rankings. These mechanisms improve consensus quality by reducing bias from aggressive discourse, and they are expected to foster higher group satisfaction through perceived fairness in deliberation. Potential improvements include benchmarking against gold standards, extending to multilingual and multimodal contexts, and enhancing transparency for end-users.\n                  <\/jats:p>","DOI":"10.1007\/s12530-026-09813-1","type":"journal-article","created":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T10:43:14Z","timestamp":1773484994000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mitigating Linguistic Aggression in Group Decision-Making: A Comparative Analysis of AI-Driven Hostility Detection"],"prefix":"10.1007","volume":"17","author":[{"given":"Jos\u00e9 Ram\u00f3n","family":"Trillo","sequence":"first","affiliation":[]},{"given":"Juan Carlos","family":"Gonz\u00e1lez-Quesada","sequence":"additional","affiliation":[]},{"given":"Francisco Javier","family":"Cabrerizo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4253-8629","authenticated-orcid":false,"given":"Ignacio Javier","family":"P\u00e9rez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,3,14]]},"reference":[{"issue":"6","key":"9813_CR1","doi-asserted-by":"publisher","first-page":"1549","DOI":"10.1007\/s00259-023-06172-w","volume":"50","author":"IL Alberts","year":"2023","unstructured":"Alberts IL, Mercolli L, Pyka T, Prenosil G, Shi K, Rominger A, Afshar-Oromieh A (2023) Large language models (llm) and chatgpt: what will the impact on nuclear medicine be? Eur J Nucl Med Mol Imaging 50(6):1549\u20131552","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"9813_CR2","first-page":"1877","volume":"33","author":"TB Brown","year":"2020","unstructured":"Brown TB (2020) otros: language models are few-shot learners. Adv Neural Inf Process Syst 33:1877\u20131901","journal-title":"Adv Neural Inf Process Syst"},{"key":"9813_CR3","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown T, Mann B, Ryder N, Subbiah M, Kaplan JD, Dhariwal P, Neelakantan A, Shyam P, Sastry G, Askell A et al (2020) Language models are few-shot learners. Adv Neural Inf Process Syst 33:1877\u20131901","journal-title":"Adv Neural Inf Process Syst"},{"key":"9813_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmps.2023.105454","volume":"181","author":"MJ Buehler","year":"2023","unstructured":"Buehler MJ (2023) Melm, a generative pretrained language modeling framework that solves forward and inverse mechanics problems. J Mech Phys Solids 181:105454","journal-title":"J Mech Phys Solids"},{"key":"9813_CR5","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1007\/s00500-009-0453-x","volume":"14","author":"FJ Cabrerizo","year":"2010","unstructured":"Cabrerizo FJ, Moreno JM, P\u00e9rez IJ, Herrera-Viedma E (2010) Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks. Soft Comput 14:451\u2013463","journal-title":"Soft Comput"},{"key":"9813_CR6","first-page":"115","volume":"255","author":"FJ Cabrerizo","year":"2014","unstructured":"Cabrerizo FJ, Ure\u00f1a R, Pedrycz W, Herrera-Viedma E (2014) Building consensus in group decision making with an allocation of information granularity 255:115\u2013127","journal-title":"Building consensus in group decision making with an allocation of information granularity"},{"key":"9813_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.124657","author":"M Darraz","year":"2025","unstructured":"Darraz M, Laour M, Guemghar S (2025) Integrated sentiment analysis with bert for enhanced recommendation systems. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2024.124657","journal-title":"Expert Syst Appl"},{"key":"9813_CR8","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (2018) Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805"},{"key":"9813_CR9","unstructured":"Gajula MVNS (2025) Sentiment-aware recommendation systems in e-commerce: A review from a natural language processing perspective. arXiv preprint arXiv:2505.03828 [cs.IR]"},{"key":"9813_CR10","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1023\/A:1010711413444","volume":"31","author":"A Gaudine","year":"2001","unstructured":"Gaudine A, Thorne L (2001) Emotion and ethical decision-making in organizations. J Bus Ethics 31:175\u2013187","journal-title":"J Bus Ethics"},{"key":"9813_CR11","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. Advances in neural information processing systems 27"},{"key":"9813_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125843","volume":"264","author":"E Hashmi","year":"2025","unstructured":"Hashmi E, Yayilgan SY, Yamin MM, Abomhara M, Ullah M (2025) Self-supervised hate speech detection in norwegian texts with lexical and semantic augmentations. Expert Syst Appl 264:125843","journal-title":"Expert Syst Appl"},{"issue":"3","key":"9813_CR13","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1109\/TSMCA.2002.802821","volume":"32","author":"E Herrera-Viedma","year":"2002","unstructured":"Herrera-Viedma E, Herrera F, Chiclana F (2002) A consensus model for multiperson decision making with different preference structures. IEEE Transactions on Systems Man and Cybernetics-Part A Systems and Humans 32(3):394\u2013402","journal-title":"IEEE Transactions on Systems Man and Cybernetics-Part A Systems and Humans"},{"key":"9813_CR14","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.inffus.2013.04.002","volume":"17","author":"E Herrera-Viedma","year":"2014","unstructured":"Herrera-Viedma E, Cabrerizo FJ, Kacprzyk J, Pedrycz W (2014) A review of soft consensus models in a fuzzy environment. Information Fusion 17:4\u201313","journal-title":"Information Fusion"},{"issue":"1","key":"9813_CR15","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1038\/s41368-023-00239-y","volume":"15","author":"H Huang","year":"2023","unstructured":"Huang H, Zheng O, Wang D, Yin J, Wang Z, Ding S, Yin H, Xu C, Yang R, Zheng Q et al (2023) Chatgpt for shaping the future of dentistry: the potential of multi-modal large language model. Int J Oral Sci 15(1):29","journal-title":"Int J Oral Sci"},{"key":"9813_CR16","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.knosys.2017.02.011","volume":"123","author":"\u00d6 Kabak","year":"2017","unstructured":"Kabak \u00d6, Ervural B (2017) Multiple attribute group decision making: A generic conceptual framework and a classification scheme. Knowl-Based Syst 123:13\u201330","journal-title":"Knowl-Based Syst"},{"issue":"1","key":"9813_CR17","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1109\/MCI.2018.2881641","volume":"14","author":"J Kacprzyk","year":"2019","unstructured":"Kacprzyk J, Yager RR, Merigo JM (2019) Towards human-centric aggregation via ordered weighted aggregation operators and linguistic data summaries: A new perspective on zadeh\u2019s inspirations. IEEE Comput Intell Mag 14(1):16\u201330","journal-title":"IEEE Comput Intell Mag"},{"issue":"1","key":"9813_CR18","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s40547-024-00143-4","volume":"11","author":"JO Krugmann","year":"2024","unstructured":"Krugmann JO, Hartmann J (2024) Sentiment analysis in the age of generative ai. Cust Needs Solut 11(1):3","journal-title":"Cust Needs Solut"},{"key":"9813_CR19","unstructured":"Kumarage T, Bhattacharjee A, Garland J (2024) Harnessing artificial intelligence to combat online hate: Exploring the challenges and opportunities of large language models in hate speech detection. arXiv preprint arXiv:2403.08035"},{"key":"9813_CR20","doi-asserted-by":"crossref","unstructured":"Levy O, Goldberg Y (2014) Dependency-based word embeddings. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 302\u2013308","DOI":"10.3115\/v1\/P14-2050"},{"key":"9813_CR21","doi-asserted-by":"publisher","first-page":"136292","DOI":"10.1109\/ACCESS.2023.3338545","volume":"11","author":"B Magalh\u00e3es","year":"2023","unstructured":"Magalh\u00e3es B, Neto A, Cunha A (2023) Generative adversarial networks for augmenting endoscopy image datasets of stomach precancerous lesions: A review. IEEE Access 11:136292\u2013136307","journal-title":"IEEE Access"},{"issue":"2","key":"9813_CR22","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1633\/JISTaP.2024.12.2.5","volume":"12","author":"G Meena","year":"2024","unstructured":"Meena G, Mohbey KK, Lokesh K (2024) Point of interest recommendation system using sentiment analysis. Journal of Information Science Theory and Practice 12(2):65\u201378. https:\/\/doi.org\/10.1633\/JISTaP.2024.12.2.5","journal-title":"Journal of Information Science Theory and Practice"},{"key":"9813_CR23","doi-asserted-by":"crossref","unstructured":"Meena G, Mohbey KK, Lokesh K (2024) Fstl-sa: Few-shot transfer learning for sentiment analysis from facial expressions. Multimedia Tools and Applications, 1\u201329","DOI":"10.1007\/s11042-024-20518-y"},{"key":"9813_CR24","doi-asserted-by":"publisher","first-page":"49963","DOI":"10.2196\/49963","volume":"25","author":"H Miao","year":"2023","unstructured":"Miao H, Li C, Wang J (2023) A future of smarter digital health empowered by generative pretrained transformer. J Med Internet Res 25:49963","journal-title":"J Med Internet Res"},{"key":"9813_CR25","unstructured":"Mirza M, Osindero S (2014) Conditional generative adversarial nets. arXiv preprint arXiv:1411.1784"},{"key":"9813_CR26","unstructured":"Mohammed IA, Venkataraman S (2023) An innovative study for the development of a wearable ai device to monitor parkinson\u2019s disease using generative ai and llm techniques. International Journal of Creative Research Thoughts (IJCRT) www. ijcrt. org, ISSN, 2320\u20132882"},{"key":"9813_CR27","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1016\/j.knosys.2018.12.006","volume":"165","author":"JA Morente-Molinera","year":"2019","unstructured":"Morente-Molinera JA, Kou G, Samuylov K, Ure\u00f1a R, Herrera-Viedma E (2019) Carrying out consensual group decision making processes under social networks using sentiment analysis over comparative expressions. Knowl-Based Syst 165:335\u2013345","journal-title":"Knowl-Based Syst"},{"key":"9813_CR28","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1016\/j.procs.2022.01.021","volume":"199","author":"JA Morente-Molinera","year":"2022","unstructured":"Morente-Molinera JA, Cabrerizo FJ, Trillo J, P\u00e9rez I, Herrera-Viedma E (2022) Managing group decision making criteria values using fuzzy ontologies. Procedia Computer Science 199:166\u2013173","journal-title":"Procedia Computer Science"},{"issue":"10","key":"9813_CR29","doi-asserted-by":"publisher","first-page":"567","DOI":"10.3390\/info14100567","volume":"14","author":"B Nicula","year":"2023","unstructured":"Nicula B, Dascalu M, Arner T, Balyan R, McNamara DS (2023) Automated assessment of comprehension strategies from self-explanations using llms. Information 14(10):567","journal-title":"Information"},{"issue":"2","key":"9813_CR30","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/0377-2217(91)90252-Q","volume":"51","author":"H Nurmi","year":"1991","unstructured":"Nurmi H, Kacprzyk J (1991) On fuzzy tournaments and their solution concepts in group decision making. Eur J Oper Res 51(2):223\u2013232","journal-title":"Eur J Oper Res"},{"key":"9813_CR31","unstructured":"Ozdemir S (2023) Quick Start Guide to Large Language Models: Strategies and Best Practices for Using ChatGPT and Other LLMs"},{"key":"9813_CR32","unstructured":"Pangtey L, Bhatnagar A, Bansal S, Dar SS, Kumar N (2025) Large language models meet stance detection: A survey of tasks, methods, applications, challenges and future directions. arXiv preprint arXiv:2505.08464"},{"issue":"9","key":"9813_CR33","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1016\/j.tics.2012.07.009","volume":"16","author":"MP Paulus","year":"2012","unstructured":"Paulus MP, Angela JY (2012) Emotion and decision-making: affect-driven belief systems in anxiety and depression. Trends Cogn Sci 16(9):476\u2013483","journal-title":"Trends Cogn Sci"},{"key":"9813_CR34","doi-asserted-by":"crossref","unstructured":"Pearce H, Tan B, Ahmad B, Karri R, Dolan-Gavitt B (2023) Examining zero-shot vulnerability repair with large language models. In: 2023 IEEE Symposium on Security and Privacy (SP), 2339\u20132356 . IEEE","DOI":"10.1109\/SP46215.2023.10179324"},{"key":"9813_CR35","doi-asserted-by":"publisher","first-page":"1617","DOI":"10.1007\/s00500-012-0975-5","volume":"17","author":"IJ P\u00e9rez","year":"2013","unstructured":"P\u00e9rez IJ, Wikstr\u00f6m R, Mezei J, Carlsson C, Herrera-Viedma E (2013) A new consensus model for group decision making using fuzzy ontology. Soft Comput 17:1617\u20131627","journal-title":"Soft Comput"},{"key":"9813_CR36","doi-asserted-by":"crossref","unstructured":"Pilehvar MT, Camacho-Collados J (2021) Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning","DOI":"10.1007\/978-3-031-02177-0"},{"issue":"10","key":"9813_CR37","first-page":"21","volume":"34","author":"S Pramanik","year":"2011","unstructured":"Pramanik S, Mukhopadhyaya D (2011) Grey relational analysis based intuitionistic fuzzy multi-criteria group decision-making approach for teacher selection in higher education. International Journal of Computer Applications 34(10):21\u201329","journal-title":"International Journal of Computer Applications"},{"key":"9813_CR38","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.inffus.2021.11.001","volume":"80","author":"J Qin","year":"2022","unstructured":"Qin J, Li M, Liang Y (2022) Minimum cost consensus model for crp-driven preference optimization analysis in large-scale group decision making using louvain algorithm. Information Fusion 80:121\u2013136","journal-title":"Information Fusion"},{"key":"9813_CR39","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.future.2020.01.005","volume":"106","author":"GA Ruz","year":"2020","unstructured":"Ruz GA, Henr\u00edquez PA, Mascare\u00f1o A (2020) Sentiment analysis of twitter data during critical events through bayesian networks classifiers. Futur Gener Comput Syst 106:92\u2013104","journal-title":"Futur Gener Comput Syst"},{"key":"9813_CR40","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.future.2020.07.050","volume":"114","author":"S Sadiq","year":"2021","unstructured":"Sadiq S, Mehmood A, Ullah S, Ahmad M, Choi GS, On B-W (2021) Aggression detection through deep neural model on twitter. Futur Gener Comput Syst 114:120\u2013129","journal-title":"Futur Gener Comput Syst"},{"issue":"2","key":"9813_CR41","first-page":"179","volume":"14","author":"L Sayegh","year":"2004","unstructured":"Sayegh L, Anthony WP, Perrew\u00e9 PL (2004) Managerial decision-making under crisis: The role of emotion in an intuitive decision process. Hum Resour Manag Rev 14(2):179\u2013199","journal-title":"Hum Resour Manag Rev"},{"issue":"1","key":"9813_CR42","first-page":"57","volume":"1","author":"HA Simon","year":"1987","unstructured":"Simon HA (1987) Making management decisions: The role of intuition and emotion. Acad Manag Exec 1(1):57\u201364","journal-title":"Acad Manag Exec"},{"issue":"4","key":"9813_CR43","doi-asserted-by":"publisher","first-page":"63","DOI":"10.58729\/1941-6679.1435","volume":"28","author":"TJ Strader","year":"2020","unstructured":"Strader TJ, Rozycki JJ, Root TH, Huang Y-HJ (2020) Machine learning stock market prediction studies: review and research directions. Journal of International Technology and Information Management 28(4):63\u201383","journal-title":"Journal of International Technology and Information Management"},{"key":"9813_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.dajour.2024.100427","volume":"10","author":"F Svenson","year":"2024","unstructured":"Svenson F, Peuser M, \u00c7etin F, Aidoo DC, Launer MA (2024) Decision-making styles and trust across farmers and bankers: Global survey results. Decision Analytics Journal 10:100427","journal-title":"Decision Analytics Journal"},{"key":"9813_CR45","volume":"191","author":"A Taghavi","year":"2020","unstructured":"Taghavi A, Eslami E, Herrera-Viedma E, Ure\u00f1a R (2020) Trust based group decision making in environments with extreme uncertainty 191:105168","journal-title":"Trust based group decision making in environments with extreme uncertainty"},{"key":"9813_CR46","doi-asserted-by":"crossref","unstructured":"Trillo JR, Cabrerizo FJ, P\u00e9rez IJ, Morente-Molinera JA, Herrera-Viedma E (2024) A new consensus reaching method for group decision-making based on the large language model gemini for detecting hostility during the discussion process. In: 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), 1\u20138 . IEEE","DOI":"10.1109\/EAIS58494.2024.10570029"},{"issue":"12","key":"9813_CR47","doi-asserted-by":"publisher","first-page":"2035","DOI":"10.3390\/math10122035","volume":"10","author":"JR Trillo","year":"2022","unstructured":"Trillo JR, Cabrerizo FJ, Chiclana F, Mart\u00ednez M\u00c1, Mata F, Herrera-Viedma E (2022) Theorem verification of the quantifier-guided dominance degree with the mean operator for additive preference relations. Mathematics 10(12):2035","journal-title":"Mathematics"},{"key":"9813_CR48","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1016\/j.inffus.2022.11.009","volume":"91","author":"JR Trillo","year":"2023","unstructured":"Trillo JR, Herrera-Viedma E, Morente-Molinera JA, Cabrerizo FJ (2023) A large scale group decision making system based on sentiment analysis cluster. Information Fusion 91:633\u2013643","journal-title":"Information Fusion"},{"issue":"9","key":"9813_CR49","doi-asserted-by":"publisher","first-page":"5796","DOI":"10.1109\/TSMC.2023.3275056","volume":"53","author":"JR Trillo","year":"2023","unstructured":"Trillo JR, Herrera-Viedma E, Morente-Molinera JA, Cabrerizo FJ (2023) A group decision-making method based on the experts\u2019 behavior during the debate. IEEE Transactions on Systems Man and Cybernetics Systems 53(9):5796\u20135808","journal-title":"IEEE Transactions on Systems Man and Cybernetics Systems"},{"key":"9813_CR50","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. Advances in neural information processing systems 30"},{"issue":"7","key":"9813_CR51","doi-asserted-by":"publisher","first-page":"5731","DOI":"10.1007\/s10462-022-10144-1","volume":"55","author":"M Wankhade","year":"2022","unstructured":"Wankhade M, Rao ACS, Kulkarni C (2022) A survey on sentiment analysis methods, applications, and challenges. Artif Intell Rev 55(7):5731\u20135780","journal-title":"Artif Intell Rev"},{"key":"9813_CR52","doi-asserted-by":"crossref","unstructured":"Yager RR, Kacprzyk J (2012) The Ordered Weighted Averaging Operators: Theory and Applications","DOI":"10.1007\/978-3-642-17910-5"},{"issue":"2","key":"9813_CR53","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/0020-0255(81)90017-7","volume":"24","author":"RR Yager","year":"1981","unstructured":"Yager RR (1981) A procedure for ordering fuzzy subsets of the unit interval. Inf Sci 24(2):143\u2013161","journal-title":"Inf Sci"},{"issue":"1","key":"9813_CR54","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1002\/(SICI)1098-111X(199601)11:1<49::AID-INT3>3.0.CO;2-Z","volume":"11","author":"RR Yager","year":"1996","unstructured":"Yager RR (1996) Quantifier guided aggregation using OWA operators. Int J Intell Syst 11(1):49\u201373","journal-title":"Int J Intell Syst"},{"key":"9813_CR55","doi-asserted-by":"crossref","unstructured":"Zhang W, Deng Y, Liu B, Pan SJ, Bing L (2023) Sentiment analysis in the era of large language models: A reality check. arXiv preprint arXiv:2305.15005","DOI":"10.18653\/v1\/2024.findings-naacl.246"},{"key":"9813_CR56","unstructured":"Zhuo H, Yang Y, Peng K (2025) Combating toxic language: A review of llm-based strategies for software engineering. arXiv preprint arXiv:2504.15439"}],"container-title":["Evolving Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-026-09813-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12530-026-09813-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-026-09813-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T10:43:19Z","timestamp":1773484999000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12530-026-09813-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,14]]},"references-count":56,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["9813"],"URL":"https:\/\/doi.org\/10.1007\/s12530-026-09813-1","relation":{},"ISSN":["1868-6478","1868-6486"],"issn-type":[{"value":"1868-6478","type":"print"},{"value":"1868-6486","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,14]]},"assertion":[{"value":"2 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 August 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 February 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 March 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no Conflict of interest related to this research.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest Statement"}}],"article-number":"47"}}