The ecological crisis made the British and American ecological literature develop rapidly in the 20th century ecological thought. As a unique literary style that expresses the relationship between nature and man, British and American ecological literature has a far-reaching romantic tradition, and returning to nature is its eternal theme and dream. The study of the romantic tradition of British and American ecological literature has important implications for the development of ecological literature and ecological criticism. British and American romantic writers wrote their own ecological consciousness from three aspects: natural aesthetic and spiritual significance, simple ecological environmental protection consciousness, and life community. They reveal the true meaning of beauty in nature, interpret the beauty of harmony in harmony with nature, advocate returning to nature and the beautiful nature of human beings, and open up a natural path leading to truth, goodness, and beauty for people to pursue their spiritual home. In addition, they also expressed their deep concern for natural resources and the natural environment and called on people to respect life and protect and rationally use natural resources. It highlights that people are not the real masters of the nature, but as an inseparable member of the nature, they form an equal community of destiny with other creatures in the world. The value of British and American romantic literature lies in revealing the deep relationship and mutual influence between human beings and nature and prompting people to comprehend the importance of protecting the ecological environment and living in harmony with nature.
In English education, British and American literature is a new type of course. The teaching of British and American literature has also undergone many reforms. In the practice of teaching reform, artificial intelligence- (AI-) assisted teaching such as machine learning (ML) has a long history. The performance is continuously improved by studying the mechanism of computer simulation of the human brain learning British and American literature. Then, computer intelligence can be realized. Based on this, this paper mainly discusses two aspects. One is the sentiment tendency analysis method based on the sentiment dictionary, and the other is the sentiment tendency analysis method based on ML. It mainly introduces the judgment of different emotional tendencies by the sentiment analysis model, which is an automatic review analysis and ensemble classification approach. The improvement of sentiment analysis improves the recognition range of text sentiment words in British and American literature teaching to optimize the process of text analysis. Its main feature is that the sentiment analysis of text directly acts on the tendency of words, with fine granularity and accurate analysis. Finally, it is concluded that the maximum value of the algorithm proposed here is 0.9, which has higher accuracy than the maximum value of 0.81 of other analysis models. The results indicate that the integrated classification model combining British and American literature teaching with the dimensions hidden Markov model has relatively reasonable text analysis and high sentiment classification accuracy. In terms of British and American literature teaching, using ML algorithms can effectively help teachers teach British and American literature through sentiment analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.