Sentiment Analysis Of Users’ Comment On Children’s Reading APP

Since the network technology is developing rapidly,more and more digital reading products continue to emerge in the children’s reading market.Moreover,there are some mobile devices are important for children’s reading,such as smartphones and tablet computers.Under the background of building "Universal Reading",children’s reading APP is the main digital reading platform for children,and the development status of its application software has a certain impact on the effective enforcement of reading for all.To improve the quality of reading,cultivate and promote children’s love of digital reading,improving the quality of digital reading applications becomes an important task.In the process of iterative development of children’s reading APP applications,there are many user online comments in application market,and it is an important part of online platform such as social media and e-commerce websites.Online comments reflect users’ opinions and attitudes towards the object being evaluated,meanwhile they are also the important information source for users to make decisions.Through online comments,users can choose a child-friendly reading platform for users,and improve the trust of children’s reading APP users in reading products.This paper takes the online comments of children’s reading APP users in the APPstore as the data source,uses web crawler technology and sentiment analysis technology to establish a topic model based on the collection of user online comment data,and mines and analyzes the comment data.The specific steps are as follows: first use Python software to collect the data,organize the collected comment data,and carry out text preprocessing processes such as deduplication,cleaning,Chinese text parting.The collated text data is analyzed according to the text sentiment dictionary,and the positive emotion comment word cloud map and the negative emotion comment word cloud map are drawn,which initially obtains the user’s attention and complaint points for the application software.Based on emotional tendency analysis results,the establishment of the LDA model of the theme,potential theme keywords are extracted from the user’s comments,and then the deeper keywords in the comments are excavated to understand the user’s demand,opinions,and emotional performance of children’s reading APP services,etc.According to the analysis results,this study gives advice on the development of children’s reading APP service from three aspects: software development and design,application content and service members,thus to further improve the quality of children’s reading.The above conclusions and recommendations,put forward to enrich the promotion of forms,stimulating independent innovation,strengthening media publicity and establishing an evaluation mechanism for the promotion of children’s digital reading is proposed.