Study on the Automatic Construction Method of Tibetan Sentiment Dictionary based on C-TF
To solve the unique challenges in the study of sentiment analysis of Tibetan languages,such as the lack of annotation data and limited language resources,an automatic construction method of Tibetan sentiment dictionary based on the combination of convolutional neural network(CNN)and Term frequency(C-TF)is pro-posed in this paper.There are many rich emotional texts in the Tibetan language.Statistical analysis was con-ducted for the sentiment words collected from eight Tibetan operas in traditional Tibetan literature combined with the word frequency in some social media comments,and emotional seed words were calculated with the com-bination of the word frequency and CNN,And then using a large-scale unlabeled data for pre-training and a small amount of labeled data for fine-tuning,a Tibetan sentiment dictionary with 12 503 emotional words is con-structed.To evaluate the accuracy of the dictionary proposed in this paper,we compared it with other dictionar-ies using the open source sentiment analysis dataset TU_SA,and the experimental results demonstrate that our method achieves significant performance improvement in the task of emotion dictionary construction.
NETL
NSTL
万方数据
