多特征融合的图文微博情感分析

现有的微博情感分析方法已经注意到了微博文本与图片之间的互补作用，但较少注意用户情感表达的差异和微博内容中除文字之外的特征，为此提出一种多特征融合的图文微博情感分析方法。首先构建文本情感分类模型，将对情感具有很好指示作用的内容特征和用户特征与微博句子进行融合， 然后构造了基于参数迁移和微调的图片情感分类模型。最后设计特征层和决策层融合的方法，将文本和图片情感分类模型进行融合。实验结果表明，内容特征和用户特征有效增强了模型捕捉情感语义的能力，并在多项性能指标上都取得了很好的效果， 构建的图文情感分类模型和融合方法可获得更好的性能。

Multimedia sentiment analysis on microblog based on multi-feature fusion

Previous studies had exploited the complementary effect between text and images in microblog sentiment analysis, but less focused on some factors such as user personality and content characteristics. To solve this problem, this paper proposed an multimedia sentiment analysis on microblog based on multi-feature fusion method. Firstly it constructed a text sentiment classification model considering the user-based features and content-based features which had a good indication of emotions. Then it constructed an image model based on parameter transfer and fine-tuned. Finally, it designed fusion method of the early fusion and the late fusion. The experimental results show that user-based features and content-based features can enhance model ability of capturing emotion semantic, and the proposed model and fusion methods get higher accuracy on the real-world test dataset.