Weibo Text Classification Based on Knowledge Graph
Yingjun Liu · Journal of Physics Conference Series · 2021
Abstract As a platform for sharing and communication, Weibo can produce a large amount of short text data every day. Because the Weibo text is short and the text features are sparse, it contains less information, serious colloquialization and weak anti-noise ability, so it is difficult to achieve the desired results by using the traditional text classification method to classify Weibo text. This paper proposes a Weibo text classification method based on knowledge graph, which uses knowledge graph to expand text semantics and enrich text features on the basis of the original Weibo text. Then the TextCNN model is used to classify Weibo texts with extended semantics. The experimental results show that the classification accuracy of this method is better than that of Weibo text classification directly.