查看文章

Nowadays, individuals spend significant time on online social networks and microblogging websites, consuming news and expressing their opinions and viewpoints on various topics. It is an excellent source of data for various data mining applications, such as sentiment analysis. Mining this type of data presents several challenges, including the posts’ short length and informal language. On the other hand, microblog posts contain a high degree of interdependence, which can help to improve sentiment classification based on text. This data can be represented as a graph, with nodes representing posts and edges representing the various relationships between them. By using recently developed deep learning models for graph structures, this approach enables efficient sentiment analysis of microblog posts. This paper utilizes graphs to represent microblog posts and their various relationships, such as user …