Dynamic Topic Evolution and Sentiment Interaction in Pacific Rim Ecological Discourse
DOI: 10.23977/langl.2025.080203 | Downloads: 13 | Views: 375
Author(s)
Ma Xiaolong 1
Affiliation(s)
1 School of Law and Humanities, China University of Mining & Technology (Beijing), 100083 Beijing, China
Corresponding Author
Ma XiaolongABSTRACT
This study investigates the dynamic characteristics of ecological discourse in Pacific Rim news and its impact on international ecosystems by integrating Latent Dirichlet Allocation (LDA) topic modeling and sentiment lexicon analysis. A time-sensitive LDA model and a hierarchical weighted sentiment analysis framework were developed to analyze English news texts from 2021 to 2025, identifying five core themes and their sentiment evolution patterns. The findings reveal a dual tension between collaborative symbiosis and competitive confrontation in ecological discourse. Positive sentiments dominate educational and economic cooperation, while negative sentiments correlate with geopolitical conflicts. Cross-evolution analysis demonstrates that discourse fluctuations stem from the interplay between the pluralistic harmony philosophy and power competition realities, highlighting structural contradictions in policy-practice decoupling and discourse power imbalance. Methodologically, this research innovates by proposing a dynamic topic-sentiment evolution framework, enhancing LDA interpretability through temporal parameters and domain-specific lexicon constraints, and bridging ecolinguistics with computational linguistics. The results offer data-driven insights for global ecological governance and advance interdisciplinary discourse analysis.
KEYWORDS
Pacific Rim news; Ecological Discourse Analysis; LDA topic modeling; sentiment interactionCITE THIS PAPER
Ma Xiaolong, Dynamic Topic Evolution and Sentiment Interaction in Pacific Rim Ecological Discourse. Lecture Notes on Language and Literature (2025) Vol. 8: 13-25. DOI: http://dx.doi.org/10.23977/langl.2025.080203.
REFERENCES
[1] Abdullah, T., Ahmet, A., 2022. Deep learning in sentiment analysis: Recent architectures. [J]. ACM Computing Surveys. 55(8), 1–37.
[2] Ainsworth, J., 2021. An ecolinguistic discourse approach to teaching environmental sustainability: Analyzing chief executive officer letters to shareholders. [J]. Business and Professional Communication Quarterly. 84 (4), 1–23.
[3] Blei, D. M., Ng, A. Y., & Jordan, M. I. 2003. Latent Dirichlet allocation. [J]. Journal of Machine Learning Research, (3), 993–1022.
[4] Cheng, X., Cao, Q., & Liao, S. S. 2022. An overview of literature on COVID-19, MERS and SARS: Using text mining and latent dirichlet allocation. [J]. Journal of Information Science, 48(3), 304–320.
[5] Zhao Changyu, Wu Yaping, Wang Jimin. Thematic mining and sentiment analysis of Twitter texts under the "Belt and Road" initiative [J]. Library and Information Science, 2019, (19), 119-127.
[6] Devika, M.D., Sunitha, C., Ganesh, A., 2016. Sentiment analysis: A comparative study on different approaches. [J]. Procedia Computer Science. 87, 44–49.
[7] Fairclough, N., 1989. Language and Power. Longman, Harlow.
[8] Wei Rong, He Wei. Construction of Intervention System Analysis Model for International Ecological Discourse [J]. Journal of PLA University of Foreign Languages, 2019, (06),91-99.
[9] Haugen, E. 1972. The ecology of language. In: Anwar, S. Dil (ed.), The ecology of language: Essays by Einar Haugen, 325-339. Stanford, CA: Stanford University Press.
[10] Li, J., Steffensen, S.V., Huang, G., 2020. Rethinking ecolinguistics from a distributed language perspective. [J]. Language Sciences. 80, 1–11.
[11] Lindstedt, N. C. 2019. Structural topic modeling for social scientists: A brief case study with social movement studies literature, 2005–2017. [J]. Social Currents, 6(4), 307–318.
[12] Liu, B., 2022. Sentiment Analysis and Opinion Mining. Springer Nature.
[13] Liu, Z., Li, M., Liu, Y., & Ponraj, M. 2011. Performance evaluation of latent dirichlet allocation in text mining, 2011 FSKD, 4, 2695–2698.
[14] Huang Guowen, Zhao Ruihua. Origin, objectives, principles and methods of ecological discourse analysis [J]. Modern Foreign Language, 2017, (05),585-596+729.
[15] McCutcheon, A. L. 1987. Latent class analysis. Newbury Park, Calif.: Sage Publications.
[16] Nelson, G.L., Carson, J., Batal, M.A., Bakary, W.E., 2002. Cross-cultural pragmatics: Strategy use in Egyptian Arabic and American English refusals. Appl. Linguist. 23 (2), 163-189.
[17] Nelson, L. K. 2020. Computational grounded theory: A methodological framework. [J]. Sociological Methods & Research, 49(1), 3–42.
[18] Peng, S., Cao, L., Zhou, Y., Ouyang, Z., Yang, A., Li, X., Jia, W., Yu, S., 2022. A survey on deep learning for textual emotion analysis in social networks. [J]. Digital Communications and Networks. 8 (5), 745–762.
[19] Poole, R., 2022. Corpus-Assisted Ecolinguistics. Bloomsbury, London.
[20] Steffensen, S.V., Fill, A., 2014. Ecolinguistics: the state of the art and future horizons. [J]. Language Sciences. 41, 6–25.
[21] Stibbe, A., 2021. Ecolinguistics: Language, Ecology and the Stories We Live By, second ed. Routledge, Abingdon-New York.
[22] Stibble, A., 2015. Ecolinguistics: Language, Ecology and the Stories we Live by. Routledge, London; New York.
[23] Tudoran, A. A. 2018. Why do internet consumers block ads? New evidence from consumer opinion mining and sentiment analysis. [J]. Internet Research, 29(1), 144–166.
[24] Wang, G., 2018. A corpus-assisted critical discourse analysis of news reporting on China's air pollution in the official Chinese English-language press. [J]. Discourse & Communication. 12 (6), 645–662.
[25] Westrupp, E. M., Greenwood, C. J., Fuller-Tyszkiewicz, M., Berkowitz, T. S., Hagg, L., & Youssef, G. 2022. Text mining of reddit posts: Using latent dirichlet allocation to identify common parenting issues. [J]. PLoS One, 17(2).
[26] Wirzba, N., 2023. The trouble with sustainability. [J]. Sustainability. 15 (2), 1388.
[27] He Wei, Wei Rong, Arran Stibbe. Interdisciplinary Development of Ecological Linguistics-Interview with Professor Aaron Stibb [J]. Foreign Language Studies, 2018a,35(02):22-26+112.
[28] He Wei, Wei Rong. Diversity and harmony, interaction and symbiosis-Construction of ecological philosophy in international ecological discourse analysis [J]. Foreign Language Journal, 2018b, (06):28-35.
[29] He Wei, Wei Rong. The connotation and research direction of international ecological discourse [J]. Foreign Language Research, 2017a, (05),18-24.
[30] He Wei, Wei Rong. Construction of an Object-oriented Analysis Model for International Ecological Discourse [J]. Modern Foreign Language, 2017b, (05),597-607+729.
[31] He Wei, Wei Rong. Ecological Linguistics: Development Process and Disciplinary Attributes [J]. Foreign Social Sciences, 2018c, (04):113-123.
[32] He Wei and Zhang Ruijie. Construction of Ecological Discourse Analysis Model [J]. Chinese Foreign Language, 2017, (05),56-64.
[33] He Liang, Li Fang. Topic discovery and trend analysis of scientific literature based on topic model [J]. Chinese Inform Journal, 2012,26 (02): 109-115.
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