Multi-Dimensional Digital Media Sentiment Visualization Intelligent Analysis System Based on Machine Learning Algorithm

This study builds a multi-dimensional sentiment analysis system to solve the problem of sentiment prediction of text and image data in the Weibo platform. By combining CNN (Convolutional Neural Network), BiLSTM (Bidirectional Long Short-Term Memory) and Attention mechanism (AM), the accuracy of sentiment classification is improved, which helps to better understand and analyze user sentiment expressions in social media. This study uses crawler tools to collect text and image data of 1,000 users on the Weibo platform from January to December 2021 to ensure the diversity and representativeness of the data; the text data is segmented, stop words are removed, and the text is converted into vectors; at the same time, the ResNet-50 pre-trained model is used to extract the deep features of the image, CNN is used to process the image data, and BiLSTM captures the contextual information in the text data. Finally, the AM is used to enhance the model's attention to emotional expression. Experimental results show that the proposed Word2Vec (Word to Vector) model performs outstandingly in the accuracy of sentiment classification. The accuracy of the CNN-BiLSTM-Attention model in positive, neutral and negative classification tasks is 97.5 per cent, 95.4 per cent and 91.6 per cent, respectively, which are significantly better than the performance of the CNN and BiLSTM models, especially in the evaluation indicators such as accuracy and macro F1. This study proposes a multimodal sentiment analysis system based on CNN-BiLSTM-Attention, which significantly and effectively improves the accuracy of social media sentiment classification. The system can effectively process complex sentiment categories and multimodal data, and has broad application prospects, especially in the fields of social media sentiment analysis and public opinion monitoring.

@article{Leia2025,
  title     = {Multi-Dimensional Digital Media Sentiment Visualization Intelligent Analysis System Based on Machine Learning Algorithm},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {5},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Mengwei Leia and Qiong Chen},
  doi       = {10.14569/IJACSA.2025.0160589},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160589}
}