{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T16:20:25Z","timestamp":1778170825848,"version":"3.51.4"},"reference-count":107,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,5,21]],"date-time":"2024-05-21T00:00:00Z","timestamp":1716249600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,5,21]],"date-time":"2024-05-21T00:00:00Z","timestamp":1716249600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/V00784X\/1"],"award-info":[{"award-number":["EP\/V00784X\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/S023305\/1"],"award-info":[{"award-number":["EP\/S023305\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Pers Ubiquit Comput"],"published-print":{"date-parts":[[2024,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>ChatGPT, a sophisticated chatbot system by OpenAI, gained significant attention and adoption in 2022 and 2023. By generating human-like conversations, it attracted over 100 million monthly users; however, there are concerns about the social impact of ChatGPT, including panic, misinformation and ethics. Twitter has become a platform for expressing views on ChatGPT and popular NLP approaches like topic modelling, sentiment analysis and emotion detection are commonly used to study public discourses on Twitter. While these approaches have limitations, an analytical process of existing best practices captures the evolving nature of these views. Previous studies have examined early reactions and topics associated with ChatGPT on Twitter but have not fully explored the combination of topics, sentiment and emotions, nor have they explicitly followed existing best practices. This study provides an overview of the views expressed on Twitter about ChatGPT by analysing 88,058 tweets from November 2022 to March 2023 to see if panic and concern were replicated in Twitter discourses. The topics covered human-like text generation, chatbot development, writing assistance, data training, efficiency, impact on business and cryptocurrency. Overall, the sentiment was predominantly positive, indicating that concerns surrounding ChatGPT were not widely replicated. However, sentiment fluctuated, with a decline observed around the launch of ChatGPT Plus. The discourse saw consistent patterns of trust and fear, with trust maintaining a steady presence until a decline potentially influenced by concerns about biases and misinformation. We discuss how our findings build upon existing research regarding ChatGPT by providing trajectories of topics, sentiment and emotions.<\/jats:p>","DOI":"10.1007\/s00779-024-01811-x","type":"journal-article","created":{"date-parts":[[2024,5,21]],"date-time":"2024-05-21T09:02:06Z","timestamp":1716282126000},"page":"875-894","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["\u201cThe ChatGPT bot is causing panic now \u2013 but it\u2019ll soon be as mundane a tool as Excel\u201d: analysing topics, sentiment and emotions relating to ChatGPT on Twitter"],"prefix":"10.1007","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1269-7004","authenticated-orcid":false,"given":"Dan","family":"Heaton","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeremie","family":"Clos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elena","family":"Nichele","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joel E.","family":"Fischer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,5,21]]},"reference":[{"issue":"1","key":"1811_CR1","first-page":"9","volume":"1","author":"AS George","year":"2023","unstructured":"George AS, George AH (2023) A review of ChatGPT AI\u2019s impact on several business sectors. Partners Univers Int Innov J 1(1):9\u201323","journal-title":"Partners Univers Int Innov J"},{"key":"1811_CR2","doi-asserted-by":"crossref","unstructured":"Ray PP (2023) ChatGPT: a comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems 3:21\u2013154","DOI":"10.1016\/j.iotcps.2023.04.003"},{"issue":"2","key":"1811_CR3","first-page":"16","volume":"15","author":"W Hariri","year":"2023","unstructured":"Hariri W (2023) Unlocking the potential of ChatGPT: a comprehensive exploration of its applications. Technology 15(2):16","journal-title":"Technology"},{"issue":"1","key":"1811_CR4","first-page":"63","volume":"12","author":"B Rathore","year":"2023","unstructured":"Rathore B (2023) Future of AI & generation alpha ChatGPT beyond boundaries. Eduzone: Int Peer Rev\/Refereed Multidiscip J 12(1):63\u201368","journal-title":"Eduzone: Int Peer Rev\/Refereed Multidiscip J"},{"key":"1811_CR5","volume-title":"How chat GPT can transform autodidactic experiences and open education","author":"M Firat","year":"2023","unstructured":"Firat M (2023) How chat GPT can transform autodidactic experiences and open education. Open Education Faculty, Anadolu Unive, Department of Distance Education"},{"key":"1811_CR6","unstructured":"Ye R (2023) The power of prompting: navigating the future of AI and machine learning. Rizwan Ye"},{"key":"1811_CR7","doi-asserted-by":"crossref","unstructured":"Ali R, Tang OY, Connolly ID, Fridley JS, Shin JH, Zadnik Sullivan PL et al (2022) Performance of ChatGPT, GPT-4, and Google bard on a neurosurgery oral boards preparation question bank. Neurosurgery 93(5):10\u20131227","DOI":"10.1227\/neu.0000000000002551"},{"key":"1811_CR8","doi-asserted-by":"crossref","unstructured":"Abdullah M, Madain A, Jararweh Y (2022) ChatGPT: fundamentals, applications and social impacts. In 2022 Ninth international conference on social networks analysis, management and security (SNAMS) 1\u20138. IEEE","DOI":"10.1109\/SNAMS58071.2022.10062688"},{"key":"1811_CR9","unstructured":"Verma P, Lerman R (2022) What is ChatGPT? Everything you need to know about chatbot from OpenAI. WP Company. Available from:\u00a0https:\/\/www.washingtonpost.com\/technology\/2022\/12\/06\/what-is-chatgpt-ai\/"},{"key":"1811_CR10","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-Pe\u00f1alvo FJ (2023) The perception of Artificial Intelligence in educational contexts after the launch of ChatGPT: disruption or panic? Education in the knowledge society 24:e31279","DOI":"10.14201\/eks.31279"},{"key":"1811_CR11","unstructured":"Roose K (2022) The brilliance and weirdness of ChatGPT. The New York Times. Accessed 17 Jun 2023. https:\/\/www.nytimes.com\/2022\/12\/05\/technology\/chatgpt-ai-twitter.html"},{"key":"1811_CR12","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1557\/s43577-023-00520-9","volume":"48","author":"MA Yatoo","year":"2023","unstructured":"Yatoo MA, Habib F (2023) ChatGPT, a friend or a foe? MRS Bull 48:310\u2013313","journal-title":"MRS Bull"},{"issue":"8","key":"1811_CR13","doi-asserted-by":"crossref","first-page":"NP654","DOI":"10.1093\/asj\/sjad093","volume":"43","author":"D Najafali","year":"2023","unstructured":"Najafali D, Camacho JM, Reiche E, Galbraith L, Morrison SD, Dorafshar AH (2023) Truth or lies? The pitfalls and limitations of ChatGPT in systematic review creation. Aesthet Surg J 43(8):NP654\u2013NP655","journal-title":"Aesthet Surg J"},{"key":"1811_CR14","doi-asserted-by":"crossref","first-page":"1166120","DOI":"10.3389\/fpubh.2023.1166120","volume":"11","author":"L De Angelis","year":"2023","unstructured":"De Angelis L, Baglivo F, Arzilli G, Privitera GP, Ferragina P, Tozzi AE et al (2023) ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health. Front Public Health 11:1166120","journal-title":"Front Public Health"},{"key":"1811_CR15","doi-asserted-by":"crossref","unstructured":"Zhou J, Muller H, Holzinger A, Chen F (2023) Ethical ChatGPT: concerns, challenges, and commandments. arXiv preprint arXiv:2305.10646","DOI":"10.3390\/electronics13173417"},{"key":"1811_CR16","doi-asserted-by":"crossref","first-page":"16","DOI":"10.58496\/MJCS\/2023\/003","volume":"2023","author":"M Aljanabi","year":"2023","unstructured":"Aljanabi M (2023) ChatGPT: future directions and open possibilities. Mesopotamian J Cybersecurity 2023:16\u201317","journal-title":"Mesopotamian J Cybersecurity"},{"key":"1811_CR17","doi-asserted-by":"crossref","unstructured":"Biswas S (2023) Will ChatGPT take my Job? Replies and advice by ChatGPT. Replies and Advice by ChatGPT. Available at https:\/\/ssrn.com\/abstract=4437405","DOI":"10.32388\/4HASUM"},{"key":"1811_CR18","doi-asserted-by":"crossref","unstructured":"Ferrara E (2023). Should ChatGPT be biased? Challenges and risks of bias in large language models. arXiv preprint arXiv:2304.03738","DOI":"10.2139\/ssrn.4627814"},{"issue":"4","key":"1811_CR19","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1080\/15265161.2023.2180110","volume":"23","author":"RH Doshi","year":"2023","unstructured":"Doshi RH, Bajaj SS, Krumholz HM (2023) ChatGPT: temptations of progress. Am J Bioeth 23(4):6\u20138","journal-title":"Am J Bioeth"},{"key":"1811_CR20","doi-asserted-by":"crossref","unstructured":"Weller K, Bruns A, Burgess J, Mahrt M, Puschmann C (Eds) (2013) Twitter and society (p 4). New York: Peter Lang","DOI":"10.3726\/978-1-4539-1170-9"},{"issue":"3","key":"1811_CR21","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1177\/0049124115605339","volume":"46","author":"TH McCormick","year":"2017","unstructured":"McCormick TH, Lee H, Cesare N, Shojaie A, Spiro ES (2017) Using Twitter for demographic and social science research: tools for data collection and processing. Sociol Methods Res 46(3):390\u2013421","journal-title":"Sociol Methods Res"},{"key":"1811_CR22","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.1007\/978-1-4614-9372-3","volume-title":"Twitter data analytics","author":"S Kumar","year":"2014","unstructured":"Kumar S, Morstatter F, Liu H (2014) Twitter data analytics. Springer, New York, pp 1041\u20134347"},{"key":"1811_CR23","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s10660-017-9257-8","volume":"18","author":"JK Rout","year":"2018","unstructured":"Rout JK, Choo KKR, Dash AK, Bakshi S, Jena SK, Williams KL (2018) A model for sentiment and emotion analysis of unstructured social media text. Electron Commer Res 18:181\u2013199","journal-title":"Electron Commer Res"},{"key":"1811_CR24","doi-asserted-by":"publisher","unstructured":"Hu A, Chancellor S, De Choudhury M (2019) Characterizing homelessness discourse on social media. In Extended abstracts of the 2019 CHI conference on human factors in computing systems, pp 1\u20136. Available from: https:\/\/doi.org\/10.1145\/3290607.3313057","DOI":"10.1145\/3290607.3313057"},{"key":"1811_CR25","doi-asserted-by":"publisher","unstructured":"Tang CL, Liao J, Wang HC, Sung CY, Cao YR, Lin WC (2020) Supporting online video learning with concept map-based recommendation of learning path. In Extended abstracts of the 2020 CHI Conference on human factors in computing systems, pp 1\u20138. Available from: https:\/\/doi.org\/10.1145\/3334480.3382943","DOI":"10.1145\/3334480.3382943"},{"key":"1811_CR26","doi-asserted-by":"publisher","unstructured":"Wang Q, Saha K, Gregori E, Joyner D, Goel A (2021) Towards mutual theory of mind in human-AI interaction: how language reflects what students perceive about a virtual teaching assistant. In Proceedings of the 2021 CHI conference on human factors in computing systems: 1\u201314. Available from: https:\/\/doi.org\/10.1145\/3411764","DOI":"10.1145\/3411764"},{"key":"1811_CR27","doi-asserted-by":"publisher","unstructured":"Jiang JA, Brubaker JR, Fiesler C (2017) Understanding diverse interpretations of animated gifs. In Proceedings of the 2017 CHI Conference extended abstracts on human factors in computing systems, pp 1726\u20131732. Available from: https:\/\/doi.org\/10.1145\/3027063.3053139","DOI":"10.1145\/3027063.3053139"},{"key":"1811_CR28","doi-asserted-by":"publisher","unstructured":"Fast E, Chen B, Bernstein MS (2016) Empath: understanding topic signals in large-scale text. In Proceedings of the 2016 CHI conference on human factors in computing systems, pp 4647\u20134657. Available from: https:\/\/doi.org\/10.1145\/2858036.2858535","DOI":"10.1145\/2858036.2858535"},{"key":"1811_CR29","doi-asserted-by":"crossref","first-page":"e1211","DOI":"10.7717\/peerj-cs.1211","volume":"9","author":"D Heaton","year":"2023","unstructured":"Heaton D, Clos J, Nichele E, Fischer J (2023) Critical reflections on three popular computational linguistic approaches to examine Twitter discourses. PeerJ Comput Sci 9:e1211","journal-title":"PeerJ Comput Sci"},{"key":"1811_CR30","unstructured":"Haque MU, Dharmadasa I, Sworna ZT, Rajapakse RN, Ahmad H (2022) \"I think this is the most disruptive technology\": exploring sentiments of ChatGPT early adopters using Twitter data. arXiv preprint arXiv:2212.05856"},{"issue":"1","key":"1811_CR31","doi-asserted-by":"crossref","first-page":"35","DOI":"10.3390\/bdcc7010035","volume":"7","author":"V Taecharungroj","year":"2023","unstructured":"Taecharungroj V (2023) \u201cWhat can ChatGPT do?\u201d Analyzing early reactions to the innovative AI Chatbot on Twitter. Big Data Cogn Comput 7(1):35","journal-title":"Big Data Cogn Comput"},{"issue":"2","key":"1811_CR32","doi-asserted-by":"crossref","first-page":"202","DOI":"10.52866\/ijcsm.2023.02.02.018","volume":"4","author":"A Korkmaz","year":"2023","unstructured":"Korkmaz A, Akt\u00fcrk C, Talan T (2023) Analyzing the user\u2019s sentiments of ChatGPT using Twitter data. Iraqi J Comput Sci Math 4(2):202\u2013214","journal-title":"Iraqi J Comput Sci Math"},{"key":"1811_CR33","doi-asserted-by":"crossref","unstructured":"Leiter C, Zhang R, Chen Y, Belouadi J, Larionov D, Fresen V et al (2023) ChatGPT: a meta-analysis after 2.5 months. arXiv preprint arXiv:2302.13795","DOI":"10.1016\/j.mlwa.2024.100541"},{"issue":"4","key":"1811_CR34","doi-asserted-by":"crossref","first-page":"100089","DOI":"10.1016\/j.tbench.2023.100089","volume":"2","author":"A Haleem","year":"2022","unstructured":"Haleem A, Javaid M, Singh RP (2022) An era of ChatGPT as a significant futuristic support tool: a study on features, abilities, and challenges. BenchCouncil Trans Benchmarks, Stand Evaluations 2(4):100089","journal-title":"BenchCouncil Trans Benchmarks, Stand Evaluations"},{"issue":"2","key":"1811_CR35","doi-asserted-by":"crossref","first-page":"62","DOI":"10.3390\/bdcc7020062","volume":"7","author":"H Hassani","year":"2023","unstructured":"Hassani H, Silva ES (2023) The role of ChatGPT in data science: how AI-assisted conversational interfaces are revolutionizing the field. Big Data Cogn Comput 7(2):62","journal-title":"Big Data Cogn Comput"},{"issue":"1","key":"1811_CR36","first-page":"1","volume":"23","author":"J Whalen","year":"2023","unstructured":"Whalen J, Mouza C (2023) ChatGPT: challenges, opportunities, and implications for teacher education. Contemp Issues Technol Teach Educ 23(1):1\u201323","journal-title":"Contemp Issues Technol Teach Educ"},{"issue":"6","key":"1811_CR37","first-page":"1","volume":"66","author":"H Chen","year":"2023","unstructured":"Chen H, Yuan K, Huang Y, Guo L, Wang Y, Chen J (2023) Feedback is all you need: from ChatGPT to autonomous driving. Sci China Inf Sci 66(6):1\u20133","journal-title":"Sci China Inf Sci"},{"issue":"2","key":"1811_CR38","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1080\/02763869.2023.2194149","volume":"42","author":"B Zhang","year":"2023","unstructured":"Zhang B (2023) ChatGPT, an opportunity to understand more about language models. Med Ref Serv Q 42(2):194\u2013201","journal-title":"Med Ref Serv Q"},{"issue":"2","key":"1811_CR39","first-page":"101","volume":"6","author":"\u0130 D\u00f6nmez","year":"2023","unstructured":"D\u00f6nmez \u0130, Sahin ID\u0130N, G\u00fclen S (2023) Conducting academic research with the AI interface ChatGPT: challenges and opportunities. J STEAM Educ 6(2):101\u2013118","journal-title":"J STEAM Educ"},{"key":"1811_CR40","doi-asserted-by":"crossref","unstructured":"Antaki F, Touma S, Milad D, El-Khoury J, Duval R (2023) Evaluating the performance of chatgpt in ophthalmology: an analysis of its successes and shortcomings. Ophthalmology Science 3(4):100324","DOI":"10.1016\/j.xops.2023.100324"},{"key":"1811_CR41","doi-asserted-by":"crossref","unstructured":"Aiyappa R, An J, Kwak H, Ahn YY (2023) Can we trust the evaluation on ChatGPT?. arXiv preprint arXiv:2303.12767","DOI":"10.18653\/v1\/2023.trustnlp-1.5"},{"key":"1811_CR42","doi-asserted-by":"crossref","unstructured":"Xie Y, Seth I, Hunter-Smith DJ, Rozen WM, Ross R, Lee M (2023) Aesthetic surgery advice and counseling from artificial intelligence: a rhinoplasty consultation with ChatGPT. Aestheti Plast Surg 47(5):1\u20139","DOI":"10.1007\/s00266-023-03338-7"},{"key":"1811_CR43","doi-asserted-by":"crossref","unstructured":"Cao Y, Zhai J (2023) Bridging the gap\u2013the impact of ChatGPT on financial research.\u00a0J Chin Econ Bus Stud 21(2):1\u201315","DOI":"10.1080\/14765284.2023.2212434"},{"issue":"7954","key":"1811_CR44","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1038\/d41586-023-00816-5","volume":"615","author":"K Sanderson","year":"2023","unstructured":"Sanderson K (2023) GPT-4 is here: what scientists think. Nature 615(7954):773","journal-title":"Nature"},{"key":"1811_CR45","unstructured":"Fezari M, Ali-Al-Dahoud AAD (2023) From GPT to AutoGPT: a brief attention in NLP processing using DL"},{"key":"1811_CR46","first-page":"1","volume":"6","author":"J Rudolph","year":"2023","unstructured":"Rudolph J, Tan S, Tan S (2023) War of the chatbots: Bard, Bing Chat, ChatGPT, Ernie and beyond. The new AI gold rush and its impact on higher education. J Appl Learn Teach 6:1","journal-title":"J Appl Learn Teach"},{"key":"1811_CR47","unstructured":"Roose K (2023) GPT-4 is exciting and scary. The New York Times, 15 Mar 2023. https:\/\/www.nytimes.com\/2023\/03\/15\/technology\/gpt-4-artificial-intelligence-openai.html"},{"key":"1811_CR48","unstructured":"Kelly SM (2022) This AI chatbot is dominating social media with its frighteningly good essays \u2014 CNN business. Cable News Network. Available from: https:\/\/edition.cnn.com\/2022\/12\/05\/tech\/chatgpt-trnd\/index.html"},{"key":"1811_CR49","doi-asserted-by":"crossref","unstructured":"Kellerman A (2023) Chatbots and information mobility: an agenda for thought and study. Environment and planning B: urban analytics and city science 50(6):1413\u20131415","DOI":"10.1177\/23998083231181595"},{"key":"1811_CR50","doi-asserted-by":"crossref","unstructured":"Ray A, Ghasemkhani H, Martinelli C (2023) Competition and cognition in the market for online news. Forthcoming, J Manag Inf Sys. Available at https:\/\/ssrn.com\/abstract=4376209","DOI":"10.2139\/ssrn.4376209"},{"issue":"1","key":"1811_CR51","doi-asserted-by":"crossref","first-page":"24","DOI":"10.5530\/bems.9.1.5","volume":"9","author":"AH Kumar","year":"2023","unstructured":"Kumar AH (2023) Analysis of ChatGPT tool to assess the potential of its utility for academic writing in biomedical domain. Biol, Eng, Med Sci Rep 9(1):24\u201330","journal-title":"Biol, Eng, Med Sci Rep"},{"key":"1811_CR52","doi-asserted-by":"crossref","unstructured":"Michaux C (2023) Can chat GPT be considered an author? I met with chat GPT and asked some questions about philosophy of art and philosophy of mind. Available at https:\/\/ssrn.com\/abstract=4439607","DOI":"10.2139\/ssrn.4439607"},{"key":"1811_CR53","unstructured":"Zhuo TY, Huang Y, Chen C, Xing Z (2023) Exploring AI ethics of ChatGPT: a diagnostic analysis. arXiv preprint arXiv:2301.12867"},{"issue":"1","key":"1811_CR54","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1021\/acsenergylett.2c02758","volume":"8","author":"AR Kirmani","year":"2022","unstructured":"Kirmani AR (2022) Artificial intelligence-enabled science poetry. ACS Energy Lett 8(1):574\u2013576","journal-title":"ACS Energy Lett"},{"key":"1811_CR55","first-page":"1","volume":"12","author":"A Shafeeg","year":"2023","unstructured":"Shafeeg A, Shazhaev I, Mihaylov D, Tularov A, Shazhaev I (2023) Voice assistant integrated with ChatGPT. Indones J Comput Sci 12:1","journal-title":"Indones J Comput Sci"},{"key":"1811_CR56","doi-asserted-by":"crossref","unstructured":"Feng Y, Vanam S, Cherukupally M, Zheng W, Qiu M, Chen H (2023) Investigating code generation performance of Chat-GPT with crowdsourcing social data. In Proceedings of the 47th IEEE Comp Softw Appl Conf, pp 1\u201310","DOI":"10.1109\/COMPSAC57700.2023.00117"},{"key":"1811_CR57","doi-asserted-by":"crossref","unstructured":"Wang S, Scells H, Koopman B, Zuccon G (2023) Can chatGPT write a good boolean query for systematic review literature search?. arXiv preprint arXiv:2302.03495","DOI":"10.1145\/3539618.3591703"},{"key":"1811_CR58","unstructured":"Kocaballi AB (2023) Conversational AI-powered design: chatGPT as designer, user, and product. arXiv preprint arXiv:2302.07406"},{"key":"1811_CR59","first-page":"3","volume":"8","author":"D Kalla","year":"2023","unstructured":"Kalla D, Smith N (2023) Study and analysis of Chat GPT and its impact on different fields of study. Int J Innov Sci Res Technol 8:3","journal-title":"Int J Innov Sci Res Technol"},{"issue":"supplement","key":"1811_CR60","first-page":"8","volume":"50","author":"S Jasanoff","year":"2020","unstructured":"Jasanoff S (2020) Temptations of technocracy in the century of engineering. Bridge 50(supplement):8\u201310","journal-title":"Bridge"},{"key":"1811_CR61","unstructured":"Tiwary N (2023) Netizens, academicians, and information professionals\u2019 opinions about AI with special reference to ChatGPT. arXiv preprint arXiv:2302.07136"},{"key":"1811_CR62","doi-asserted-by":"crossref","unstructured":"Khalil M, Er E (2023) Will ChatGPT get you caught? Rethinking of plagiarism detection. arXiv preprint arXiv:2302.04335","DOI":"10.35542\/osf.io\/fnh48"},{"key":"1811_CR63","doi-asserted-by":"crossref","unstructured":"Hartmann J, Schwenzow J, Witte M (2023) The political ideology of conversational AI: converging evidence on ChatGPT's pro-environmental, left-libertarian orientation. arXiv preprint arXiv:2301.01768","DOI":"10.2139\/ssrn.4316084"},{"key":"1811_CR64","unstructured":"Whannel K (2022) Could a chatbot answer prime minister\u2019s questions? BBC. Available from: https:\/\/www.bbc.co.uk\/news\/uk-politics-64053550"},{"key":"1811_CR65","doi-asserted-by":"publisher","unstructured":"Fischer JE (2023) Generative AI considered harmful. In: Proceedings of the 5th International conference on conversational user interfaces. CUI \u201923: pp 1\u20135. Available from https: https:\/\/doi.org\/10.1145\/3571884.3603756","DOI":"10.1145\/3571884.3603756"},{"key":"1811_CR66","unstructured":"Agarwal A, Xie B, Vovsha I, Rambow O, Passonneau RJ (2011) Sentiment analysis of twitter data. In Proceedings of the workshop on language in social media (LSM 2011):30\u201338"},{"key":"1811_CR67","doi-asserted-by":"crossref","unstructured":"Jianqiang Z (2015) Pre-processing boosting Twitter sentiment analysis?. In 2015 IEEE international conference on smart City\/SocialCom\/SustainCom (SmartCity): pp 748\u2013753. IEEE","DOI":"10.1109\/SmartCity.2015.158"},{"key":"1811_CR68","doi-asserted-by":"crossref","unstructured":"Chong WY, Selvaretnam B, Soon L (2014) Natural language processing for sentiment analysis: an exploratory analysis on tweets. In 2014 4th international conference on artificial intelligence with applications in engineering and technology, pp 212\u2013217. IEEE","DOI":"10.1109\/ICAIET.2014.43"},{"key":"1811_CR69","unstructured":"Woodfield K, Morrell G, Metzler K, Blank G, Salmons J, Finnegan J, Lucraft M (2013) Blurring the Boundaries? New social media, new social research: developing a network to explore the issues faced by researchers negotiating the new research landscape of online social media platforms. NCRM"},{"issue":"1","key":"1811_CR70","doi-asserted-by":"crossref","first-page":"205630511876336","DOI":"10.1177\/2056305118763366","volume":"4","author":"C Fiesler","year":"2018","unstructured":"Fiesler C, Proferes N (2018) \u201cParticipant\u201d perceptions of Twitter research ethics. Soc Media + Soc 4(1):2056305118763366","journal-title":"Soc Media + Soc"},{"key":"1811_CR71","doi-asserted-by":"crossref","first-page":"38","DOI":"10.12688\/f1000research.3-38.v2","volume":"3","author":"CM Rivers","year":"2014","unstructured":"Rivers CM, Lewis BL (2014) Ethical research standards in a world of big data. F1000Research 3:38","journal-title":"F1000Research"},{"key":"1811_CR72","doi-asserted-by":"crossref","unstructured":"Webb H, Jirotka M, Stahl BC, Housley W, Edwards A, Williams M et al (2017) The ethical challenges of publishing Twitter data for research dissemination. In Proceedings of the 2017 ACM on web science conference, pp 339\u2013348","DOI":"10.1145\/3091478.3091489"},{"key":"1811_CR73","unstructured":"Roesslein J (2009) Tweepy documentation. 2009. Tweepy Documentation v3, 5"},{"issue":"1","key":"1811_CR74","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1177\/0165551515617393","volume":"43","author":"SI Nikolenko","year":"2017","unstructured":"Nikolenko SI, Koltcov S, Koltsova O (2017) Topic modelling for qualitative studies. J Inf Sci 43(1):88\u2013102","journal-title":"J Inf Sci"},{"key":"1811_CR75","unstructured":"\u0158eh\u016f\u0159ek R, Sojka P (2011) Gensim\u2014statistical semantics in python. Retrieved from genism.org https:\/\/api.semanticscholar.org\/CorpusID:64026679"},{"issue":"1","key":"1811_CR76","doi-asserted-by":"crossref","first-page":"012033","DOI":"10.1088\/1757-899X\/482\/1\/012033","volume":"482","author":"AF Hidayatullah","year":"2019","unstructured":"Hidayatullah AF, Hidayatullah AF, Aditya SK, Karimah Gardini ST (2019) Topic modeling of weather and climate condition on twitter using latent dirichlet allocation (LDA). In IOP Conf Ser: Mater Sci Eng 482(1):012033 (IOP Publishing)","journal-title":"In IOP Conf Ser: Mater Sci Eng"},{"issue":"Supplement_4","key":"1811_CR77","doi-asserted-by":"crossref","first-page":"ckz186","DOI":"10.1093\/eurpub\/ckz186.317","volume":"29","author":"S Song","year":"2019","unstructured":"Song S, Min J, Kim H, Min K (2019) Topic modeling to mind illegal compensation for occupational injuries. Eur J Public Health 29(Supplement_4):ckz186-317","journal-title":"Eur J Public Health"},{"key":"1811_CR78","doi-asserted-by":"publisher","unstructured":"Sengupta S (2019) What are academic subreddits talking about? A comparative analysis of r\/academia and r\/gradschool. In Conference companion publication of the 2019 on computer supported cooperative work and social computing, pp 357\u2013361. Available from: https:\/\/doi.org\/10.1145\/3311957","DOI":"10.1145\/3311957"},{"issue":"1","key":"1811_CR79","first-page":"167","volume":"25","author":"J Cushing","year":"2009","unstructured":"Cushing J, Hastings R (2009) Introducing computational linguistics with NLTK (natural language toolkit). J Comput Sci Coll 25(1):167\u2013169","journal-title":"J Comput Sci Coll"},{"key":"1811_CR80","doi-asserted-by":"crossref","first-page":"62","DOI":"10.3389\/frai.2020.00062","volume":"3","author":"D Nguyen","year":"2020","unstructured":"Nguyen D, Liakata M, DeDeo S, Eisenstein J, Mimno D, Tromble R et al (2020) How we do things with words: analyzing text as social and cultural data. Front Artif Intell 3:62","journal-title":"Front Artif Intell"},{"issue":"4","key":"1811_CR81","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1016\/j.asej.2014.04.011","volume":"5","author":"W Medhat","year":"2014","unstructured":"Medhat W, Hassan A, Korashy H (2014) Sentiment analysis algorithms and applications: a survey. Ain Shams Eng J 5(4):1093\u20131113","journal-title":"Ain Shams Eng J"},{"issue":"2010","key":"1811_CR82","first-page":"627","volume":"2","author":"B Liu","year":"2010","unstructured":"Liu B (2010) Sentiment analysis and subjectivity. Handb Nat Lang Process 2(2010):627\u2013666","journal-title":"Handb Nat Lang Process"},{"issue":"1","key":"1811_CR83","first-page":"485","volume":"4","author":"VK Chauhan","year":"2018","unstructured":"Chauhan VK, Bansal A, Goel A (2018) Twitter sentiment analysis using vader. Int J Adv Res, Ideas Innov Technol (IJARIIT) 4(1):485\u2013489","journal-title":"Int J Adv Res, Ideas Innov Technol (IJARIIT)"},{"issue":"5","key":"1811_CR84","doi-asserted-by":"crossref","first-page":"4452","DOI":"10.11591\/ijece.v9i5.pp4452-4459","volume":"9","author":"VD Chaithra","year":"2019","unstructured":"Chaithra VD (2019) Hybrid approach: naive bayes and sentiment VADER for analyzing sentiment of mobile unboxing video comments. Int J Electr Comput Eng (IJECE) 9(5):4452\u20134459","journal-title":"Int J Electr Comput Eng (IJECE)"},{"key":"1811_CR85","doi-asserted-by":"publisher","unstructured":"Park J, Ciampaglia GL, Ferrara E (2016) Style in the age of Instagram: predicting success within the fashion industry using social media. In Proceedings of the 19th ACM Conference on computer-supported cooperative work & social computing, pp 64\u201373. Available from: https:\/\/doi.org\/10.1145\/2818048.2820065","DOI":"10.1145\/2818048.2820065"},{"key":"1811_CR86","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1155\/2015\/715730","volume":"2015","author":"B Agarwal","year":"2015","unstructured":"Agarwal B, Mittal N, Bansal P, Garg S (2015) Sentiment analysis using common-sense and context information. Comput Intell Neurosci 2015:30\u201330","journal-title":"Comput Intell Neurosci"},{"issue":"4","key":"1811_CR87","first-page":"251524592110472","volume":"4","author":"AL Howard","year":"2021","unstructured":"Howard AL (2021) A guide to visualizing trajectories of change with confidence bands and raw data. Adv Methods Pract Psychol Sci 4(4):25152459211047228","journal-title":"Adv Methods Pract Psychol Sci"},{"issue":"1","key":"1811_CR88","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1609\/icwsm.v5i1.14171","volume":"5","author":"J Bollen","year":"2011","unstructured":"Bollen J, Mao H, Pepe A (2011) Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena. Proc Int AAAI Conf Web Soc Media 5(1):450\u2013453","journal-title":"Proc Int AAAI Conf Web Soc Media"},{"issue":"3","key":"1811_CR89","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1111\/j.1467-8640.2012.00460.x","volume":"29","author":"SM Mohammad","year":"2013","unstructured":"Mohammad SM, Turney PD (2013) Crowdsourcing a word\u2013emotion association lexicon. Comput Intell 29(3):436\u2013465","journal-title":"Comput Intell"},{"issue":"1","key":"1811_CR90","doi-asserted-by":"crossref","first-page":"49","DOI":"10.31315\/telematika.v18i1.4341","volume":"18","author":"AS Aribowo","year":"2021","unstructured":"Aribowo AS, Khomsah S (2021) Implementation of text mining for emotion detection using the lexicon method (case study: tweets about COVID-19). Telematika: J Informatika dan Teknologi Informasi 18(1):49\u201360","journal-title":"Telematika: J Informatika dan Teknologi Informasi"},{"key":"1811_CR91","doi-asserted-by":"crossref","unstructured":"Mathur A, Kubde P, Vaidya S (2020) Emotional analysis using Twitter data during pandemic situation: COVID-19. In 2020 5th international conference on communication and electronics systems (ICCES), pp 845\u2013848. IEEE","DOI":"10.1109\/ICCES48766.2020.9138079"},{"issue":"1","key":"1811_CR92","first-page":"012016","volume":"1339","author":"V Balakrishnan","year":"2019","unstructured":"Balakrishnan V, Martin MC, Kaur W, Javed A, Javed A (2019) A comparative analysis of detection mechanisms for emotion detection. J Phys: Conf Ser 1339(1):012016 (IOP Publishing)","journal-title":"J Phys: Conf Ser"},{"key":"1811_CR93","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.procs.2019.09.157","volume":"159","author":"V Balakrishnan","year":"2019","unstructured":"Balakrishnan V, Kaur W (2019) String-based multinomial Na\u00efve Bayes for emotion detection among Facebook diabetes community. Procedia Comput Sci 159:30\u201337","journal-title":"Procedia Comput Sci"},{"key":"1811_CR94","unstructured":"Fujioka T, Bertero D, Homma T, Nagamatsu K (2019) Addressing ambiguity of emotion labels through meta-learning. arXiv preprint arXiv:1911.02216"},{"key":"1811_CR95","doi-asserted-by":"publisher","unstructured":"Heitmann M, Siebert C, Hartmann J, Schamp C (2020) More than a feeling: Benchmarks for sentiment analysis accuracy. In More than a Feeling: Benchmarks for sentiment analysis accuracy: Heitmann, Mark. (July 31, 2020). https:\/\/doi.org\/10.2139\/ssrn.3489963","DOI":"10.2139\/ssrn.3489963"},{"key":"1811_CR96","doi-asserted-by":"crossref","unstructured":"Post G, Visser V, Buis J (2017) 13. Reflection. In: Academic skills for interdisciplinary studies. Amsterdam University Press, pp 116\u2013123","DOI":"10.1515\/9789048533947-016"},{"key":"1811_CR97","doi-asserted-by":"crossref","first-page":"114155","DOI":"10.1016\/j.eswa.2020.114155","volume":"167","author":"A Alamoodi","year":"2021","unstructured":"Alamoodi A, Zaidan BB, Zaidan AA, Albahri OS, Mohammed K, Malik RQ et al (2021) Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: a systematic review. Expert Syst Appl 167:114155","journal-title":"Expert Syst Appl"},{"key":"1811_CR98","unstructured":"Gonz\u00e1lez-Ib\u00e1nez R, Muresan S, Wacholder N (2011) Identifying sarcasm in twitter: a closer look. In Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies, pp 581\u2013586"},{"key":"1811_CR99","unstructured":"Maier D, Waldherr A, Miltner P, Wiedemann G, Niekler A, Keinert A, et al. (2021) Applying LDA topic modeling in communication research: toward a valid and reliable methodology. In Computational methods for communication science, pp 13\u201338. Routledge"},{"key":"1811_CR100","first-page":"28","volume":"1","author":"S Maclean","year":"2016","unstructured":"Maclean S (2016) A new model for social work reflection: whatever the weather. Prof Soc Work 1:28\u201329","journal-title":"Prof Soc Work"},{"issue":"5","key":"1811_CR101","first-page":"360","volume":"37","author":"AJ Viera","year":"2005","unstructured":"Viera AJ, Garrett JM (2005) Understanding interobserver agreement: the kappa statistic. Fam Med 37(5):360\u2013363","journal-title":"Fam Med"},{"key":"1811_CR102","doi-asserted-by":"crossref","unstructured":"Ante L, Demir E (2023) The ChatGPT effect on AI-themed cryptocurrencies. Available at https:\/\/ssrn.com\/abstract=4350557","DOI":"10.2139\/ssrn.4350557"},{"key":"1811_CR103","doi-asserted-by":"crossref","unstructured":"Saggu A, Ante L (2023) The influence of ChatGPT on artificial intelligence related crypto assets: evidence from a synthetic control analysis. Finance Res Lett 55, 103993","DOI":"10.1016\/j.frl.2023.103993"},{"key":"1811_CR104","unstructured":"Pak A, Paroubek P (2010) Twitter as a corpus for sentiment analysis and opinion mining. In LREc 10, No. 2010:1320\u20131326"},{"key":"1811_CR105","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511981395","volume-title":"Corpus linguistics: method, theory and practice","author":"T McEnery","year":"2011","unstructured":"McEnery T, Hardie A (2011) Corpus linguistics: method, theory and practice. Cambridge University Press"},{"issue":"2","key":"1811_CR106","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1177\/0957926593004002002","volume":"4","author":"N Fairclough","year":"1993","unstructured":"Fairclough N (1993) Critical discourse analysis and the marketization of public discourse: the universities. Discourse Soc 4(2):133\u2013168","journal-title":"Discourse Soc"},{"issue":"1","key":"1811_CR107","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1075\/bjl.11.03dij","volume":"11","author":"TA Van Dijk","year":"1997","unstructured":"Van Dijk TA (1997) What is political discourse analysis. Belg J Linguist 11(1):11\u201352","journal-title":"Belg J Linguist"}],"container-title":["Personal and Ubiquitous Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00779-024-01811-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00779-024-01811-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00779-024-01811-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,28]],"date-time":"2024-12-28T08:04:34Z","timestamp":1735373074000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00779-024-01811-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,21]]},"references-count":107,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,12]]}},"alternative-id":["1811"],"URL":"https:\/\/doi.org\/10.1007\/s00779-024-01811-x","relation":{},"ISSN":["1617-4909","1617-4917"],"issn-type":[{"value":"1617-4909","type":"print"},{"value":"1617-4917","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,21]]},"assertion":[{"value":"18 July 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 May 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 May 2024","order":3,"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 no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}