A survey of text aspect-based sentiment classification

Journal of Hebei University of Science and Technology

Yunfeng XU¹  Yi YANG¹  Shengwang LI¹  Yan ZHANG¹ 

[1] School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, Hebei 050018, China;

关键词: natural language processing;    sentiment classification;    aspect-based;    text classification;    deep learning;    graph neural network;    graph convolutional network;   

DOI  :  10.7535/hbkd.2020yx06006

来源: DOAJ

【 摘 要 】

With the development of deep learning, aspect-based sentiment classification has achieved a lot of results in a single field and a single language, but there is room for improvement in multi-fields. By summarizing up the methods of text aspect-based sentiment classification in recent years, the specific application scenarios of sentiment classification were introduced, and the commonly used data sets of aspect-based sentiment classification were categorized. The development of aspect-based sentiment classification were summarized and prospected, and further research can be carried out in the following areas: exploring methods based on graph neural networks to make up for the limitations of deep learning methods; learning to fuse multi-modal data to enrich the emotional information of a single text; developing more targeted research work on multilingual texts and low-resource languages.

【 授权许可】

Unknown