{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:56:16Z","timestamp":1785286576887,"version":"3.55.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T00:00:00Z","timestamp":1724976000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T00:00:00Z","timestamp":1724976000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soc. Netw. Anal. Min."],"DOI":"10.1007\/s13278-024-01340-8","type":"journal-article","created":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T17:02:11Z","timestamp":1725037331000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Hidden emotional trends on social media regarding the Thailand\u2013China high-speed railway project: a deep learning approach with ChatGPT integration"],"prefix":"10.1007","volume":"14","author":[{"given":"Manussawee","family":"Nokkaew","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwankamol","family":"Nongpong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tapanan","family":"Yeophantong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pattravadee","family":"Ploykitikoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weerachai","family":"Arjharn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duangkamol","family":"Phonak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Apirat","family":"Siritaratiwat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chayada","family":"Surawanitkun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,8,30]]},"reference":[{"issue":"01","key":"1340_CR1","doi-asserted-by":"publisher","first-page":"317","DOI":"10.3126\/unityj.v3i01.43335","volume":"3","author":"S Adhikari","year":"2022","unstructured":"Adhikari S (2022) Social media and its impacts in human minds. Unity J 3(01):317\u2013330. https:\/\/doi.org\/10.3126\/unityj.v3i01.43335","journal-title":"Unity J"},{"key":"1340_CR2","unstructured":"Airesearch (2021) Thailand artificial intelligence research institute. https:\/\/airesearch.in.th\/releases\/wangchanberta-pre-trained-thai-language-model\/. Accessed 1 3 2024"},{"issue":"1","key":"1340_CR3","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1093\/joc\/jqac034","volume":"73","author":"E Amsalem","year":"2023","unstructured":"Amsalem E, Zoizner A (2023) Do people learn about politics on social media? a meta-analysis of 76 studies. J Commun 73(1):3\u201313. https:\/\/doi.org\/10.1093\/joc\/jqac034","journal-title":"J Commun"},{"key":"1340_CR4","unstructured":"APEC Thailand (2022) Retrieved July 3, 2024, from https:\/\/en.wikipedia.org\/wiki\/APEC_Thailand_2022"},{"key":"1340_CR5","doi-asserted-by":"publisher","first-page":"110404","DOI":"10.1016\/j.asoc.2023.110404","volume":"143","author":"S Aslan","year":"2023","unstructured":"Aslan S (2023) A deep learning-based sentiment analysis approach (MF-CNN-BILSTM) and topic modeling of tweets related to the Ukraine-Russia conflict. Appl Soft Comput 143:110404. https:\/\/doi.org\/10.1016\/j.asoc.2023.110404","journal-title":"Appl Soft Comput"},{"issue":"1","key":"1340_CR6","doi-asserted-by":"publisher","first-page":"103152","DOI":"10.1016\/j.ipm.2022.103152","volume":"60","author":"R Cao","year":"2023","unstructured":"Cao R, Liu XF, Fang Z, Xiao-Ke X, Wang X (2023) How do scientific papers from different journal tiers gain attention on social media? Inf Process Manag 60(1):103152. https:\/\/doi.org\/10.1016\/j.ipm.2022.103152","journal-title":"Inf Process Manag"},{"key":"1340_CR7","doi-asserted-by":"publisher","first-page":"113423","DOI":"10.1016\/j.jbusres.2022.113423","volume":"155","author":"J Chen","year":"2023","unstructured":"Chen J, Liu L (2023) Social media usage and entrepreneurial investment: an information-based view. J Bus Res 155:113423. https:\/\/doi.org\/10.1016\/j.jbusres.2022.113423","journal-title":"J Bus Res"},{"key":"1340_CR8","unstructured":"China-Laos Railway (2024) The China-Laos Railway Retrieved July 3, 2024 from https:\/\/en.wikipedia.org\/wiki\/Boten%E2%80%93Vientiane_railway"},{"key":"1340_CR9","volume-title":"China\u2019s belt and road initiative in ASEAN: growing presence recent progress and future challenges","year":"2022","unstructured":"Chirathivat S, Rutchatorn B, Devendrakumar A (eds) (2022) China\u2019s belt and road initiative in ASEAN: growing presence recent progress and future challenges. World Scientific, Singapore"},{"key":"1340_CR10","unstructured":"Devlin J, Chang MW, Lee K, Toutanova K (2018) Bert: Pre-training of deep bidirectional transformers for language understanding. Preprint at arXiv: 1810.04805."},{"key":"1340_CR11","doi-asserted-by":"publisher","first-page":"113707","DOI":"10.1016\/j.dss.2021.113707","volume":"162","author":"SP Eslami","year":"2022","unstructured":"Eslami SP, Ghasemaghaei M, Hassanein K (2022) Understanding consumer engagement in social media: the role of product lifecycle. Decis Support Syst 162:113707. https:\/\/doi.org\/10.1016\/j.dss.2021.113707","journal-title":"Decis Support Syst"},{"key":"1340_CR12","doi-asserted-by":"publisher","first-page":"91","DOI":"10.24507\/icicel.17.01.91","volume":"17","author":"P Gatchalee","year":"2023","unstructured":"Gatchalee P, Waijanya S, Promrit N (2023) Thai text classification experiment using CNN and transformer models for timely-timeless content marketing. ICIC Express Lett 17:91\u2013101. https:\/\/doi.org\/10.24507\/icicel.17.01.91","journal-title":"ICIC Express Lett"},{"key":"1340_CR13","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/j.tbs.2022.10.007","volume":"30","author":"S-E Kang","year":"2023","unstructured":"Kang S-E, Kim T (2023) The influence of YouTube content on travelers\u2019 intentions to use hyperloop trains: using trust transfer theory. Travel Behav Soc 30:281\u2013290","journal-title":"Travel Behav Soc"},{"key":"1340_CR14","unstructured":"Kemp S (2024) DataReportal, Kepios, 31 1 2024. https:\/\/datareportal.com\/ Accessed 1 2 2024"},{"issue":"2","key":"1340_CR15","doi-asserted-by":"publisher","first-page":"155","DOI":"10.18267\/j.aip.155","volume":"10","author":"N Khamphakdee","year":"2021","unstructured":"Khamphakdee N, Seresangtakul P (2021) Sentiment analysis for Thai language in hotel domain using machine learning algorithms. Acta Inform Prag 10(2):155\u2013171. https:\/\/doi.org\/10.18267\/j.aip.155","journal-title":"Acta Inform Prag"},{"key":"1340_CR16","doi-asserted-by":"publisher","first-page":"90","DOI":"10.3390\/data8050090","volume":"8","author":"N Khamphakdee","year":"2023","unstructured":"Khamphakdee N, Seresangtakul P (2023) An efficient deep learning for Thai sentiment analysis. Data 8:90. https:\/\/doi.org\/10.3390\/data8050090","journal-title":"Data"},{"key":"1340_CR17","doi-asserted-by":"publisher","first-page":"12334","DOI":"10.3390\/su151612334","volume":"15","author":"RA Komakech","year":"2023","unstructured":"Komakech RA, Ombati TO (2023) Belt and road initiative in developing countries: lessons from five selected countries in Africa. Sustainability 15:12334. https:\/\/doi.org\/10.3390\/su151612334","journal-title":"Sustainability"},{"key":"1340_CR18","doi-asserted-by":"publisher","first-page":"78","DOI":"10.3390\/info12020078","volume":"12","author":"H-J Kwon","year":"2021","unstructured":"Kwon H-J, Ban H-J, Jun J-K, Kim H-S (2021) Topic modeling and sentiment analysis of online review for airlines. Information 12:78. https:\/\/doi.org\/10.3390\/info12020078","journal-title":"Information"},{"issue":"10","key":"1340_CR19","doi-asserted-by":"publisher","first-page":"e10894","DOI":"10.1016\/j.heliyon.2022.e10894","volume":"8","author":"N Leelawat","year":"2022","unstructured":"Leelawat N, Jariyapongpaiboon S, Promjun A, Boonyarak S, Saengtabtim K, Laosunthara A, Yudha AK, Tang J (2022) Twitter data sentiment analysis of tourism in Thailand during the COVID-19 pandemic using machine learning. Heliyon 8(10):e10894. https:\/\/doi.org\/10.1016\/j.heliyon.2022.e10894","journal-title":"Heliyon"},{"key":"1340_CR20","unstructured":"Lowphansirikul L, Polpanumas C, Jantrakulchai N, Nutanong S (2021) WangchanBERTa: pretraining transformer-based Thai language models. Preprint at ArXiv, abs\/2101.09635"},{"issue":"1","key":"1340_CR21","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1111\/rsp3.12632","volume":"15","author":"C Maathuis","year":"2023","unstructured":"Maathuis C, Kerkhof I (2023) The first two months in the war in Ukraine through topic modeling and sentiment analysis. Reg Sci Policy Pract 15(1):56\u201374","journal-title":"Reg Sci Policy Pract"},{"key":"1340_CR22","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1057\/s41254-022-00271-5","volume":"19","author":"B Mathayomchan","year":"2023","unstructured":"Mathayomchan B, Taecharungroj V, Wattanacharoensil W (2023) Evolution of COVID-19 tweets about Southeast Asian countries: topic modelling and sentiment analyses. Place Brand Public Dipl 19:317\u2013334. https:\/\/doi.org\/10.1057\/s41254-022-00271-5","journal-title":"Place Brand Public Dipl"},{"key":"1340_CR23","doi-asserted-by":"crossref","unstructured":"Mehta T, Deshmukh G (2022) YouTube ad view sentiment analysis using deep learning and machine learning. Preprint at arXiv:2205.11082","DOI":"10.5120\/ijca2022922078"},{"key":"1340_CR24","doi-asserted-by":"publisher","DOI":"10.3389\/fcomp.2021.775368","volume":"3","author":"RK Mishra","year":"2021","unstructured":"Mishra RK, Urolagin S, Jothi JAA, Neogi AS, Nawaz N (2021) Deep learning-based sentiment analysis and topic modeling on tourism during Covid-19 pandemic. Front Comput Sci 3:775368","journal-title":"Front Comput Sci"},{"key":"1340_CR25","doi-asserted-by":"publisher","first-page":"156151","DOI":"10.1109\/ACCESS.2021.3129329","volume":"9","author":"MF Mridha","year":"2021","unstructured":"Mridha MF, Keya AJ, Hamid MA, Monowar MM, Rahman MS (2021) A comprehensive review on fake news detection with deep learning. IEEE Access 9:156151\u2013156170. https:\/\/doi.org\/10.1109\/ACCESS.2021.3129329","journal-title":"IEEE Access"},{"key":"1340_CR26","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/s13278-021-00776-6","volume":"11","author":"P Nandwani","year":"2021","unstructured":"Nandwani P, Verma R (2021) A review on sentiment analysis and emotion detection from text. Soc Netw Anal Min 11:81. https:\/\/doi.org\/10.1007\/s13278-021-00776-6","journal-title":"Soc Netw Anal Min"},{"key":"1340_CR27","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/s13278-023-01168-8","volume":"14","author":"M Nokkaew","year":"2024","unstructured":"Nokkaew M, Nongpong K, Yeophantong T et al (2024) Analyzing online public opinion on Thailand-China high-speed train and Laos-China railway mega-projects using advanced machine learning for sentiment analysis. Soc Netw Anal Min 14:15. https:\/\/doi.org\/10.1007\/s13278-023-01168-8","journal-title":"Soc Netw Anal Min"},{"key":"1340_CR28","doi-asserted-by":"publisher","first-page":"4157","DOI":"10.3390\/s22114157","volume":"22","author":"NJ Prottasha","year":"2022","unstructured":"Prottasha NJ, Sam AA, Kowsher M, Murad SA, Bairagi AK, Masud M, Baz M (2022) Transfer learning for sentiment analysis using BERT based supervised fine-tuning. Sensors 22:4157. https:\/\/doi.org\/10.3390\/s22114157","journal-title":"Sensors"},{"key":"1340_CR29","doi-asserted-by":"publisher","first-page":"5","DOI":"10.3390\/mti7010005","volume":"7","author":"CMQ Ramos","year":"2023","unstructured":"Ramos CMQ, Cardoso PJS, Fernandes HCL, Rodrigues JMF (2023) A decision-support system to analyse customer satisfaction applied to a tourism transport servic. Multimodal Technol Interact 7:5. https:\/\/doi.org\/10.3390\/mti7010005","journal-title":"Multimodal Technol Interact"},{"key":"1340_CR30","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1007\/s13278-023-01048-1","volume":"13","author":"P Rita","year":"2023","unstructured":"Rita P, Ant\u00f3nio N, Afonso A (2023) Social media discourse and voting decisions influence: sentiment analysis in tweets during an electoral period. Soc Netw Anal Min 13:46. https:\/\/doi.org\/10.1007\/s13278-023-01048-1","journal-title":"Soc Netw Anal Min"},{"key":"1340_CR31","doi-asserted-by":"publisher","first-page":"121306","DOI":"10.1016\/j.techfore.2021.121306","volume":"175","author":"V Schulhof","year":"2022","unstructured":"Schulhof V, van Vuuren D, Kirchherr J (2022) The belt and road initiative (BRI): what will it look like in the future? Technol Forecast Soc Change 175:121306","journal-title":"Technol Forecast Soc Change"},{"key":"1340_CR32","doi-asserted-by":"publisher","first-page":"100345","DOI":"10.1016\/j.puhip.2022.100345","volume":"4","author":"G Sesa","year":"2022","unstructured":"Sesa G, Czabanowska K, Giangreco A, Middleton J (2022) Addressing COVID-19 vaccine hesitancy: a content analysis of government social media platforms in England and Italy during 2020\u20132021. Pub Health Pract 4:100345. https:\/\/doi.org\/10.1016\/j.puhip.2022.100345","journal-title":"Pub Health Pract"},{"key":"1340_CR33","unstructured":"Shajari S, Agarwal N, Alassad M (2023) Commenter behavior characterization on YouTube channels. Preprint at arXiv:2304.07681"},{"key":"1340_CR34","doi-asserted-by":"publisher","DOI":"10.4324\/9781003399834","volume-title":"Belt and road initiative and South Asia","year":"2023","unstructured":"Sharma KR (ed) (2023) Belt and road initiative and South Asia, 1st edn. Routledge, London. https:\/\/doi.org\/10.4324\/9781003399834","edition":"1"},{"key":"1340_CR35","unstructured":"State Railway of Thailand (2022) www.railway.co.th Accessed 1 12 2023"},{"key":"1340_CR36","doi-asserted-by":"publisher","first-page":"204","DOI":"10.3390\/info12050204","volume":"12","author":"C Villavicencio","year":"2021","unstructured":"Villavicencio C, Macrohon JJ, Inbaraj XA, Jeng J-H, Hsieh J-G (2021) Twitter sentiment analysis towards COVID-19 vaccines in the Philippines using Na\u00efve Bayes. Information 12:204. https:\/\/doi.org\/10.3390\/info12050204","journal-title":"Information"},{"issue":"1","key":"1340_CR37","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1080\/17538068.2022.2054196","volume":"16","author":"Y Wang","year":"2023","unstructured":"Wang Y, Chen Y (2023) Characterizing discourses about COVID-19 vaccines on Twitter: a topic modeling and sentiment analysis approach. J Commun Healthc 16(1):103\u2013112. https:\/\/doi.org\/10.1080\/17538068.2022.2054196","journal-title":"J Commun Healthc"},{"issue":"1","key":"1340_CR38","doi-asserted-by":"publisher","first-page":"98","DOI":"10.35609\/jber.2021.6.1(3)","volume":"6","author":"S Wei","year":"2021","unstructured":"Wei S, Sukhotu V (2021) Trade promotion from Thailand to China as a result of a new train route. J Bus Econ Rev 6(1):98\u2013111. https:\/\/doi.org\/10.35609\/jber.2021.6.1(3)","journal-title":"J Bus Econ Rev"},{"issue":"2","key":"1340_CR39","doi-asserted-by":"publisher","first-page":"101684","DOI":"10.1016\/j.giq.2022.101684","volume":"39","author":"C Wukich","year":"2022","unstructured":"Wukich C (2022) Social media engagement forms in government: a structure-content framework. Gov Inf Q 39(2):101684. https:\/\/doi.org\/10.1016\/j.giq.2022.101684","journal-title":"Gov Inf Q"},{"key":"1340_CR40","doi-asserted-by":"publisher","first-page":"105796","DOI":"10.1016\/j.ssci.2022.105796","volume":"153","author":"Q Yao","year":"2022","unstructured":"Yao Q, Li RYM, Song L (2022) Construction safety knowledge sharing on YouTube from 2007 to 2021: two-step flow theory and semantic analysis. Saf Sci 153:105796. https:\/\/doi.org\/10.1016\/j.ssci.2022.105796","journal-title":"Saf Sci"},{"issue":"8","key":"1340_CR41","doi-asserted-by":"publisher","first-page":"e10146","DOI":"10.1016\/j.heliyon.2022.e10146","volume":"8","author":"G Yavetz","year":"2022","unstructured":"Yavetz G, Aharony N (2022) The users\u2019 point of view: towards a model of government information behavior on social media. Heliyon 8(8):e10146. https:\/\/doi.org\/10.1016\/j.heliyon.2022.e10146","journal-title":"Heliyon"},{"issue":"1","key":"1340_CR42","doi-asserted-by":"publisher","first-page":"101775","DOI":"10.1016\/j.giq.2022.101775","volume":"40","author":"YP Yuan","year":"2023","unstructured":"Yuan YP, Dwivedi YK, Tan GWH, Cham TH, Ooi KB, Aw ECX, Currie W (2023) Government digital transformation: understanding the role of government social media. Gov Inf Q 40(1):101775. https:\/\/doi.org\/10.1016\/j.giq.2022.101775","journal-title":"Gov Inf Q"}],"container-title":["Social Network Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-024-01340-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13278-024-01340-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-024-01340-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T05:42:36Z","timestamp":1740462156000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13278-024-01340-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,30]]},"references-count":42,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["1340"],"URL":"https:\/\/doi.org\/10.1007\/s13278-024-01340-8","relation":{},"ISSN":["1869-5469"],"issn-type":[{"value":"1869-5469","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,30]]},"assertion":[{"value":"23 April 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 July 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 August 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2024","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 competing interests that could have influenced the research question, experimental design, data collection, interpretation of results or the conclusions drawn in the current study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"175"}}