Evaluation of Sentiment Analysis in College English Writing Teaching Strategies

Abstract

The popularity of emotion analysis has led to a rapid increase in the range of remarks. This study explores the potential of sentiment analysis to enhance collegiate English writing instruction. This is achieved by methodically gathering and examining performance statistics, instructor remarks, and student feedback. However, interpreting the vast majority of comments to determine people's sentiments is challenging. Sentiment analysis (SA) is a rapid, simple, and automated method for determining the thoughts and emotions of individuals. This essay scrutinizes the objective of sentiment analysis, assesses diverse methodologies, delves into the domains where sentiment analysis finds its application, pinpoints the obstacles and constraints students face, and proposes potential solutions. The study proposed the use of sentiment analysis to examine college English writing instruction strategies using the Gradient Function Optimization (SGFO) algorithm. The results demonstrate that the participants' use of emotion terms improved significantly with the suggested approach. Those with more skill demonstrated greater benefits from the SGFO algorithm. The tool support, which enables them to use emotion phrases in their work more skillfully, also made the participants happy. The suggested model yielded the maximum accuracy of 98.5%, precision of 84%, and recall of 95%, according to the study's findings.