# Deep Learning-Driven Public Opinion Analysis on the Weibo Topic about AI Art
## 1 Introduction
Different from lexicon-based methods, machine learning-based methods involve extracting text features and designing classifiers. To examine the antivaccine topic on X, [PERSON] et al. [6] utilized the Naive Bayes algorithm for sentiment analysis, followed by topic modeling using LDA. Their findings provide feedback on people's attitudes and opinions on the COVID-19 vaccine for policymakers. [PERSON] et al. [7] analyzed tweets discussing the distribution of palliatives by the Nigerian government during COVID-19. They used the SVM classifier to categorize tweets into fine-grained sentiments, and a word cloud was utilized to provide a comprehensive view of people's attitudes, providing public opinion references to the authorities for the revision and promotion of related policies. To explore the public's perception of the utilization of ICT in government operations, [PERSON] et al. [8] utilized Naive Bayes to conduct sentiment analysis of related tweets, followed by topic modeling using LDA. Their results provide useful insights into the usage and development of e-government. With the development of deep learning technologies, deep neural networks and pre-training models have been utilized to enhance the performance of sentiment analysis models. [PERSON] et al. [9] collected college students' opinions from multiple Chinese social platforms and constructed a CNN-based sentiment classification network to conduct sentiment analysis on trending topics discussed by students. They summarized trending discussions on different platforms manually, aiming to help university administrators inform decisions related to these trending topics. [PERSON] et al. [10] studied tweets on the topic of climate change, and constructed a framework for analyzing public opinions combining both sentiment analysis and metadata analysis, thereby providing a correlation analysis between the two. [PERSON] et al. [11] utilized Weibo posts during the COVID-19 outbreak in early 2020. They conducted sentiment analysis using the ERNIE pre-training model and developed a visualization system, offering public health departments a tool for tracking the evolution of public opinion. Focusing on the topic of ChatGPT, [PERSON] and [PERSON] [12]conducted sentiment analysis using multiple pre-training models, followed by a topic classifier to provide a comprehensive view of the public's sentiments towards ChatGPT. With the emergence of AI Art technology, there is a growing interest in analyzing the impact of the technology, as well as the public's attitudes towards it. In ref. [13], the authors analyze the impact of AI Art on artists. They collected comments from various artists on AI Art technology and argued that AI Art needs to be regulated for its development. In ref. [14], the authors collected literature related to generative AI and discussed the potential ethical implications of AI Art. In ref. [15], the authors studied tweets related to generative AI models. By utilizing topic modeling and sentiment analysis, a comparison between occupations and the topic analysis was conducted, offering insights for comprehending the varying attitudes of different occupations. In ref. [16], the authors conducted surveys to interview the general public and performed an empirical analysis to examine the public's attitude towards AI Art, arguing that it is a double-edged sword. Through the analysis of related works, sentiment analysis is frequently integrated with topic analysis; however, the results of these analyses are typically reported independently. Aiming to enhance the result of sentiment analysis and provide a more comprehensive view of public opinion, this paper integrates text sentiment analysis with text clustering analysis to develop a framework for analyzing public opinion on the Weibo topic related to AI Art. The contributions of this work are outlined as follows:  
1. A public opinion analysis was conducted on the Weibo platform with the aim of acquiring Weibo users' opinions about AI Art.