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We advocate enhancing public opinion influence through \u201cgreen-oriented\u201d strategies, developing high-quality new media products, and maintaining a green ecology for user communities. Network security serves as the foundation of this ecology. This paper proposes a deep learning-based sentiment classification method for social media users, which incorporates word position information, leverages self-attention mechanisms to extract features, and optimizes outputs through batch normalization, fostering a virtuous cycle in the network environment. Experiments show that this model improves evaluation metrics by 15.31% compared to traditional models, demonstrating superior EPC performance in network security research. This highlights the positive impact of a green and healthy social media atmosphere on media usage.<\/p>","DOI":"10.4018\/ijec.372205","type":"journal-article","created":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T20:16:57Z","timestamp":1743711417000},"page":"1-22","source":"Crossref","is-referenced-by-count":0,"title":["The Construction of a Green Network Ecosystem"],"prefix":"10.4018","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0169-6817","authenticated-orcid":true,"given":"Wenzhe","family":"Wang","sequence":"first","affiliation":[{"name":"Henan Police College, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2432","reference":[{"key":"IJeC.372205-0","doi-asserted-by":"publisher","DOI":"10.1145\/2502081.2502282"},{"key":"IJeC.372205-1","unstructured":"Chang, Y. C., Chu, C. H., Chen, C. C., & Hsu, W. L. (2016, Jun). Linguistic template extraction for recognizing reader-emotion. 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