Abstract
This paper describes a study that built a neural network prediction model based on feature extraction, focusing on text analysis and image analysis of WeChat official accounts reading quantity. Based on the embedding method of the deep learning model, we extracted the text features in the title and the image features in the cover picture, explored the relationship between these features and the reading quantity, and built a neural network model based on these features to predict the reading quantity. The results show that there is a phenomenon of sentiment fusion in the text, and a sentence vector model based on Doc2Vec and a neural network model both had a good performance. This paper proposes a tool that can predict the reading quantity in advance and help administrators adjust the titles and images according to the predicted results.
Highlights
Social media platforms, such as Twitter and Facebook, provide opportunities for people to create, communicate, and share ideas
Our study focuses on text analysis and image analysis of WeChat official accounts reading quantity, which contributes to the research in this specific field and addresses this research gap
The results show that the mean average error (MAE) was 0.207, the mean square error (MSE) was 0.059, and the relative error was 34.9%, which indicates that the model had a good performance
Summary
Social media platforms, such as Twitter and Facebook, provide opportunities for people to create, communicate, and share ideas. Previous research on WeChat has focused on user behaviors and attitudes as well as the influence mechanism and communication power of WeChat as a social media platform. It involves user satisfaction, user attitude, user intention [2-5], user engagement behavior [6-7], and the influence mechanism and effect of WeChat as an information communication platform on service provided by users [8-11]. As far as we know, there has been little research on the analysis of the cover image of WeChat official accounts. Our study focuses on text analysis and image analysis of WeChat official accounts reading quantity, which contributes to the research in this specific field and addresses this research gap. We built a neural network model based on these features to predict the reading quantity of articles
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