Sentiment Distribution of Topic Discussion in Online English Learning: An Approach Based on Clustering Algorithm and Improved CNN

Sentiment Distribution of Topic Discussion in Online English Learning: An Approach Based on Clustering Algorithm and Improved CNN

Qiujuan Yang, Jiaxiao Zhang
DOI: 10.4018/IJITSA.325791
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Abstract

Online English teaching resources have recently surged, highlighting the exigency for efficient organization and categorization. This manuscript introduces an innovative strategy to classify university-level English teaching resources, employing a sophisticated density clustering algorithm. Initially, student discourse was mined within a teaching platform comment section, and in-depth textual analysis was conducted. Subsequently, the term frequency-inverse document frequency (TF–IDF) feature extraction algorithm was enhanced, while emotive attributes were seamlessly integrated into the textual manifestation layer during the classification procedure. This enabled the distribution of topics and emotions to be acquired for each comment, facilitating subsequent analyses of emotion feature extraction and model training. An improved weight calculation was designed based on TF–IDF to evaluate the importance of feature items for each corpus file. The simulation results demonstrate the proposed scheme's effectiveness. The algorithm facilitates faster scholarly access to educational resource information and effectively classifies data for high research adaptability.
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Introduction

English is an essential component of China’s basic education system. As international economic trade becomes more frequent, English is no longer simply a subject but a vital communication tool. Improving the effectiveness of English teaching in universities and enabling students to acquire English proficiency more efficiently is a topic of ongoing research. While traditional classroom teaching has the advantage of conveying knowledge quickly, it falls short in consolidating and reinforcing students’ impressions, particularly regarding language learning, which benefits from exposure to a suitable language environment. The emergence of online English teaching, made possible by the rapid development of Internet technology, has revolutionized distance learning, breaking down time and space constraints and greatly enhancing the learning experience. As a result, online learning has become a significant reform direction for university-level English teaching. Using the Internet, teachers can provide students with a wealth of diverse learning resources, encouraging their enthusiasm for learning. Furthermore, online learning platforms facilitate listening, reading, and conversation, improving the practicality of English and enhancing students’ language application abilities.

As network technology advances and the information age emerges, the demand for online teaching resources has expanded significantly. The core purpose of educational resources is to provide relevant services for learners and maximize their utilization value through reasonable classification (Colangelo et al., 2018). Misclassifying teaching resources not only reduces their educational value but also results in the wastage of human and material resources. Hence, teachers and students in basic education urgently need scientifically organized and managed education and teaching resources. Moreover, the development of online English teaching has spurred the construction of educational resource platforms, which play a vital role in the education informatization process. Currently, most college and university teachers use online platforms to provide discussion areas where students can express their doubts and opinions. Teachers can dynamically adjust teaching content, plans, and focus based on content in their online platform’s student comment section. However, although the relevant educational resource platforms have reached a certain level of development, many shortcomings remain regarding their application effects. The openness of teaching platforms leads to an uncontrollable level of user access, making it challenging for teachers to sort out and summarize comment content. In this context, analyzing teaching resources based on topic discussion and sentiment analysis can enable the fuller and more effective use of online teaching resources. This is important in promoting the comprehensive reform of basic education in China and enhancing its degree of informatization (Bustos et al., 2020; Newman & Joyner, 2018; Yadollahi et al., 2017).

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