[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-124702-105":59,"doc-detail-124702-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","sentiment-analysis-in-environmental-sustainability-field-by-machine-learning-exploratory-study","Sentiment Analysis in Environmental Sustainability Field by Machine Learning - Exploratory Study","","Environmental sustainability is a major topic of the last decade, supported by growing public awareness and education about natural resources and environmental protection. Sustainability is framed through four pillars: human, social, economic, and environmental. With Twitter widely reflecting public discussion, the study uses machine learning sentiment analysis to mine Thai social-media opinions in the environmental sustainability domain. It includes linguistic analysis, preprocessing, feature extraction, and model construction to classify positive, negative, and neutral sentiments, revealing mostly positive discussion patterns.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/sentiment-analysis-in-environmental-sustainability-field-by-machine-learning-exploratory-study/124702/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/sentiment-analysis-in-environmental-sustainability-field-by-machine-learning-exploratory-study/124702.png","ImageObject",300,407,{"name":92,"@type":93},"Finn","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-28","2026-08-05",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the main objective of the exploratory study?","Question",{"text":113,"@type":114},"To conduct social media opinion mining in the environmental sustainability field for Thai people.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Which social media platform and dataset source does the study focus on?",{"text":118,"@type":114},"Twitter, using collected posts to analyze public conversations related to environment and sustainability.",{"name":120,"@type":111,"acceptedAnswer":121},"How does the study determine sentiment categories?",{"text":122,"@type":114},"By applying machine learning sentiment analysis, including data preprocessing, feature extraction, and model construction to classify positive, negative, and neutral sentiments.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},124702,1785893998,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":8,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":81},549768064778,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","154 ENVIRONMENTAL AND ENERGY POLICIES AND FRAMEWORKS  \n[https://doi.org/10.7250/CONECT.2023.122](https://doi.org/10.7250/CONECT.2023.122)  \nSENTIMENT ANALYSIS IN ENVIRONMENTAL SUSTAINABILITY FIELD BY MACHINE LEARNING  \nKunyanuth KULARBPHETTONG1*, Phanu WARAPORN2,  \nPattarapan ROONRAKWIT3  \n1, 2 Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok, Thailand  \n3 Faculty of Information and Communication Technology, Silpakorn University, Bangkok, Thailand  \n* [Corresponding author.](Corresponding author. E-mail address: kunyanuth.ku@ssru.ac.th)[ E-mail address: kunyanuth.ku@ssru.ac.th](Corresponding author. E-mail address: kunyanuth.ku@ssru.ac.th)  \nAbstract – Environmental sustainability is one of the influential topics of the last decade. Most people have become more environmentally aware and educated environmentally conscious. Sustainability concerns the sustainability of natural resources and environmental protection. The four pillars of sustainability include human, social, economic and environmental. Twitter is a popular social media platform that keeps us updated on the latest news, events and trends from around the world. In 2022, the number of Twitter users in Thailand reached around  \n11.45 million, accounting for 16.4 % of all Thai people. Also, the fastest growing conversation in Twitter is related to the environment and sustainability. Nowadays, customers pay attention to the environmental and social impact of products they buy. Sentiment Analysis is the process of analyzing emotions or feelings by using machine learning techniques. The main objective of this exploratory study is to conduct social media opinion mining in case of the environmental sustainability field of Thai people. The paper presents the linguistic analysis of the collected data and explains discovered phenomena, including data preprocessing steps, feature extraction, and model construction to determine positive, negative and neutral sentiments. The result reveals that sentiment analysis takes place around the sustainability context mostly in positive terms to make a better understanding of the dynamics and changes in environmental sustainability society.  \nKeywords –Awareness; environmental sustainability; environmental protection;  \nmachine learning; sentiment analysis  \nAcknowledgement  \nThe authors gratefully acknowledge the financial subsidy provided by Suan Sunandha Rajabhat University.","cbCairOdFsuNgjrA","https://ap.wps.com/l/cbCairOdFsuNgjrA","pdf",231681,"English","# Abstract\n## Methods\n## Sentiment Classification\n## Results\n## Acknowledgement","[{\"question\":\"What is the main objective of the exploratory study?\",\"answer\":\"To conduct social media opinion mining in the environmental sustainability field for Thai people.\"},{\"question\":\"Which social media platform and dataset source does the study focus on?\",\"answer\":\"Twitter, using collected posts to analyze public conversations related to environment and sustainability.\"},{\"question\":\"How does the study determine sentiment categories?\",\"answer\":\"By applying machine learning sentiment analysis, including data preprocessing, feature extraction, and model construction to classify positive, negative, and neutral sentiments.\"}]","Sentiment Analysis in Environmental Sustainability Field by Machine Learning - Exploratory Study | PDF"]