{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T00:21:14Z","timestamp":1769300474042,"version":"3.49.0"},"reference-count":28,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,1,26]],"date-time":"2025-01-26T00:00:00Z","timestamp":1737849600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Humanity and Social Science Foundation of Ministry of Education of China","award":["18YJA630037"],"award-info":[{"award-number":["18YJA630037"]}]},{"name":"Humanity and Social Science Foundation of Ministry of Education of China","award":["21YJA630054"],"award-info":[{"award-number":["21YJA630054"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>This paper applies the concept of symmetry to the design of a research methodology for public opinion evolution, emphasizing that both the construction and analysis processes of the method embody symmetrical principles. In today\u2019s information age, dominated by social media, online platforms have become crucial venues for information dissemination. While the free flow of information promotes public participation, it also introduces certain challenges. Therefore, analyzing the evolution of public opinion and extracting public sentiment holds significant practical value for managing online public sentiment. This study takes the Zibo barbecue incident as a case study, utilizing the two-dimensional theory of emotion and Top2Vec for thematic analysis of public opinion comments. By combining sentiment dictionary methods with the RoBERTa model, we conduct a sentiment polarity analysis of public opinion comments. The results show that the RoBERTa model achieved an accuracy of 98.46% on the test set. The proposed method effectively uncovers public sentiment biases and the influencing factors on public emotions during the evolution of public opinion events, providing a more comprehensive understanding of the emotional dynamics throughout the development of public sentiment. This deeper insight aids in addressing issues related to public opinion more effectively.<\/jats:p>","DOI":"10.3390\/sym17020190","type":"journal-article","created":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T04:59:10Z","timestamp":1737953950000},"page":"190","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Public Opinion Evolution Based on the Two-Dimensional Theory of Emotion and Top2Vec-RoBERTa"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-9912-6475","authenticated-orcid":false,"given":"Shaowen","family":"Wang","sequence":"first","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou 311300, China"}]},{"given":"Qingyang","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Informatics, Georg-August-Universit\u00e4t G\u00f6ttingen, 37073 G\u00f6ttingen, Germany"}]},{"given":"Yanrong","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou 311300, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8175-264X","authenticated-orcid":false,"given":"Hongjiu","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou 311300, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e20080","DOI":"10.1016\/j.heliyon.2023.e20080","article-title":"Spatiotemporal pattern evolution and influencing factors of online public opinion\u2014Evidence from the early-stage of COVID-19 in China","volume":"9","author":"Wang","year":"2023","journal-title":"Heliyon"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ren, S., Gong, C., Zhang, C., and Li, C. (2023). Public opinion communication mechanism of public health emergencies in Weibo: Take the COVID-19 epidemic as an example. Front. Public Health, 11.","DOI":"10.3389\/fpubh.2023.1276083"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"9144231","DOI":"10.1155\/2022\/9144231","article-title":"Analysis of Sports Popular Trend Based on Public Opinion Mining of New Media","volume":"2022","author":"Xie","year":"2022","journal-title":"Math. Probl. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhang, C., Ma, N., and Sun, G. (2022). Using Grounded Theory to Identify Online Public Opinion in China to Improve Risk Management\u2014The Case of COVID-19. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph192214754"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"10853","DOI":"10.1007\/s00500-022-07082-z","article-title":"The role of big data in network public opinion within the colleges and universities","volume":"26","author":"Xu","year":"2022","journal-title":"Soft Comput."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1539","DOI":"10.3233\/JIFS-230246","article-title":"Intelligence system for sentiment classification with deep topic embedding using N-gram based topic modeling","volume":"45","author":"Smitha","year":"2023","journal-title":"J. Intell. Fuzzy Syst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.future.2017.09.048","article-title":"Sentiment analysis of Chinese micro-blog text based on extended sentiment dictionary","volume":"81","author":"Zhang","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"102495","DOI":"10.1016\/j.ijhm.2020.102495","article-title":"Hotel selection driven by online textual reviews: Applying a semantic partitioned sentiment dictionary and evidence theory","volume":"88","author":"Nie","year":"2020","journal-title":"Int. J. Hosp. Manag."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"32280","DOI":"10.1109\/ACCESS.2022.3160172","article-title":"A study of the application of weight distributing method combining sentiment dictionary and TF-IDF for text sentiment analysis","volume":"10","author":"Liu","year":"2022","journal-title":"IEEE Access"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Stefanis, C., Giorgi, E., Kalentzis, K., Tselemponis, A., Nena, E., Tsigalou, C., Kontogiorgis, C., Kourkoutas, Y., Chatzak, E., and Dokas, I. (2023). Sentiment analysis of epidemiological surveillance reports on COVID-19 in Greece using machine learning models. Front. Public Health, 11.","DOI":"10.3389\/fpubh.2023.1191730"},{"key":"ref_11","first-page":"5527","article-title":"Multi-tier sentiment analysis of social media text using supervised machine learning","volume":"74","author":"Rahman","year":"2023","journal-title":"Comput. Mater. Contin"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Hokijuliandy, E., Napitupulu, H. (2023). Application of SVM and Chi-Square Feature Selection for Sentiment Analysis of Indonesia\u2019s National Health Insurance Mobile Application. Mathematics, 11.","DOI":"10.3390\/math11173765"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/JCIT.335524","article-title":"Social Recommender System Based on CNN Incorporating Tagging and Contextual Features","volume":"26","author":"Alrashidi","year":"2024","journal-title":"J. Cases Inf. Technol. (JCIT)"},{"key":"ref_14","unstructured":"Devlin, J. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"107104","DOI":"10.1016\/j.asoc.2021.107104","article-title":"Sequence encoding incorporated CNN model for Email document sentiment classification","volume":"102","author":"Liu","year":"2021","journal-title":"Appl. Soft Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"118710","DOI":"10.1016\/j.eswa.2022.118710","article-title":"Social media-based COVID-19 sentiment classification model using Bi-LSTM","volume":"212","author":"Arbane","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"115119","DOI":"10.1016\/j.eswa.2021.115119","article-title":"Multilingual evaluation of pre-processing for BERT-based sentiment analysis of tweets","volume":"181","author":"Pota","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"45229","DOI":"10.1109\/ACCESS.2024.3381515","article-title":"Text Sentiment Analysis of Douban Film Short Comments Based on BERT-CNN-BiLSTM-Att Model","volume":"12","author":"He","year":"2024","journal-title":"IEEE Access"},{"key":"ref_19","first-page":"993","article-title":"Latent dirichlet allocation","volume":"3","author":"Blei","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"826","DOI":"10.1016\/j.procs.2023.08.057","article-title":"Exploring the current situation of cultural tourism scenic spots based on LDA model\u2014Take Nanjing, Jiangsu Province, China as an example","volume":"221","author":"Zhao","year":"2023","journal-title":"Procedia Comput. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1016\/j.procs.2023.01.071","article-title":"Topic Modelling and Opinion Analysis On Climate Change Twitter Data Using LDA And BERT Model","volume":"218","author":"Uthirapathy","year":"2023","journal-title":"Procedia Comput. Sci."},{"key":"ref_22","first-page":"155","article-title":"A study on the classification of research topics based on COVID-19 academic research using Topic modeling","volume":"28","author":"Yoo","year":"2022","journal-title":"J. Intell. Inf. Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1037\/h0077714","article-title":"A circumplex model of affect","volume":"39","author":"Russell","year":"1980","journal-title":"J. Personal. Soc. Psychol."},{"key":"ref_24","unstructured":"Angelov, D. (2020). Top2vec: Distributed representations of topics. arXiv."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"McInnes, L., Healy, J., and Melville, J. (2018). Umap: Uniform manifold approximation and projection for dimension reduction. arXiv.","DOI":"10.21105\/joss.00861"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"205","DOI":"10.21105\/joss.00205","article-title":"hdbscan: Hierarchical density based clustering","volume":"2","author":"McInnes","year":"2017","journal-title":"J. Open Source Softw."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"36645","DOI":"10.1109\/ACCESS.2021.3062875","article-title":"Investigating COVID-19 news across four nations: A topic modeling and sentiment analysis approach","volume":"9","author":"Ghasiya","year":"2021","journal-title":"IEEE Access"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1080\/02699939208411068","article-title":"An argument for basic emotions","volume":"6","author":"Ekman","year":"1992","journal-title":"Cogn. Emot."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/2\/190\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T10:36:24Z","timestamp":1759919784000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/2\/190"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,26]]},"references-count":28,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["sym17020190"],"URL":"https:\/\/doi.org\/10.3390\/sym17020190","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,26]]}}}