基于深度学习的藏文舆情分析研究  

Research on Tibetan Public Opinion Analysis Based on Deep Learning

作　　者：公保加羊 拉玛杰 官却多杰 索南多杰 Gongbao Jiayang;La Majie;Guanque Duojie;Suonan Duojie(Hainan Prefecture Tibetan Information Technology Research Center of Qinghai Province,Gonghe 813099,China)

机构地区：[1]青海省海南州藏文信息技术研究中心,共和813099

出　　处：《青海科技》2023年第1期56-60,共5页Qinghai Science and Technology

基　　金：青海省重点研发与转化计划—科技成果转化专项项目“‘云藏’高效爬虫及检索系统优化与集成”(2020-GX-164)。

摘　　要：随着自然语言处理技术的快速发展,藏文信息处理技术也取得了较大进展。其中,藏文舆情分析作为藏族地区社会舆情分析的重要技术,受到广泛关注。但是,现有的藏文文本情感分析研究由于起步较晚,还存在很大提升空间。本文提出基于深度集成学习的藏文文本情感分析算法。并通过建立藏文情感数据集进行实验,本文算法在三类情感(正向、负向、中性)中精确率平均提升1.65%,召回率提升1.63%,F1分数提升1.96%。实验结果表明,本文采用的深度集成学习有效地提高了文本情感分类的性能。With the rapid development of natural language processing technology, Tibetan information processing technology has also made great progress. Among them, Tibetan public opinion analysis, as an important technology for social public opinion analysis in Tibetan areas, has received widespread attention. However, due to the late start of the existing Tibetan text sentiment analysis research, there is still a lot of room for improvement. This paper proposes a Tibetan text sentiment analysis algorithm based on deep ensemble learning. Moreover, through the establishment of Tibetan emotion datasets for experiments, the algorithm in this paper has an average increase of 1.65% in precision, 1.63% in recall, and 1.96% in F1 scores in the three types of emotions(positive, negative, and neutral).

关 键 词：藏文信息处理 藏文舆情分析 文本情感分析 深度集成学习 藏文情感数据集 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391.1[自动化与计算机技术—控制科学与工程]