Sentiment Analysis And Visual Representation Of Online Learning Product Reviews

The sentiment analysis of online learning product reviews can fully express the user's experience emotions,provide users with more efficient value references,and achieve a win-win situation for users,suppliers,and platforms.E-learning product reviews are the user's subjective impressions of product content based on user experience,and often contain users' value judgments and emotional tendencies towards products.These emotions enable e-learning products to better obtain market demand feedback during development,indicate the direction of product optimization,and provide suggestions for e-learning product users when selecting products,improve the quality and efficiency of user selection,and e-learning The platform can further optimize the way in which platform products are provided based on the emotional expression of user comments and increase user stickiness.However,at present,the analysis and utilization of sentiment for online learning product reviews are not enough.Only textual display of literal meanings is performed,and there is less in-depth mining of user emotions.In the display,only general texts and scores are used to express,Did not give full play to the value of comment resources.Therefore,it is necessary to conduct sentiment analysis on the reviews of online learning products and display them in a visual way.Based on the understanding of the theory and research status of e-learning and sentiment analysis,this article explains the concepts and scope of the e-learning products and e-learning product reviews,and adopts online observation,questionnaire surveys,etc.Comment on the status quo of sentiment analysis for research.Then,taking the Chinese University MOOC platform as the research object,it analyzes the text features of online learning product reviews and performs deep cleaning on the acquired data,extracts the sentiment features of product reviews for the domain and short text attributes of the reviews,and establishes the domain sentiment in combination with the review attributes Dictionary,and through the establishment of an online learning product review sentiment analysis model,analyze the sentiment tendency of reviews,and finally quantify the sentiment tendency and visually display it in the form of radar charts.