摘要
本文利用朴素贝叶斯算法实现在线评论情感倾向分析。首先,利用爬虫获取数据,然后对数据进行预处理;其次,对在线评论文本采用jieba分词后,进行了文本分析与词频统计;使用朴素贝叶斯分类器构造一个基于朴素贝叶斯的情感分类模型,对模型进行训练后,使用有声阅读app的用户评价进行情感分析,得到在线评论情感倾向结果。
In this paper,we use the plain Bayesian algorithm to realize the analysis of online comment sentiment tendency.Firstly,the crawler was used to obtain the data,and then the data was preprocessed;secondly,the text analysis and word frequency statistics were carried out after jieba segmentation was applied to the text of the online reviews;a plain Bayesian classifier was used to construct a sentiment classification model based on plain Bayes,and after the model was trained,the user evaluations of audiobook reading apps were used for the sentiment analysis,and the results of the online reviews′sentiment tendency were obtained.
作者
王菁驿
WANG Jingyi(School of Management,Guangxi Minzu University,Nanning 530000,China)
出处
《智能计算机与应用》
2024年第4期180-183,共4页
Intelligent Computer and Applications
