摘要
随着旅游经济的到来,游客们更加关注旅游体验,本文采用BERT文本情感分析模型以及网络文本分析方法,以苏州拙政园景区为研究对象,爬取并整理携程网中游客对景区的评论信息。利用Python软件建立改进的BERT情感分析模型,训练集与测试集M值达0.94,同时针对负面评论信息使用社会和语义网络,分析游客的旅游体验特征,对景区存在的问题提供一定建议。
With the development of the tourism economy,tourists pay more attention to the tourism experience.This paper uses the text sentiment analysis model based on BERT and the web text analysis method,taking the Humble Administrator Garden as the research object,crawling and sorts out the tourist’s comments on the scenic spot in Ctrip.Python is used to build an improved BERT model,the M value of the training set and the test set is about 0.94,at the same time,in response to the negative comments of tourists,a social and semantic network was was used to analyze the characteristics of tourists’travel experience and provide certain suggestions for problems in the scenic spot.
作者
蔡汶兴
李兴东
CAI Wenxing;LI Xingdong(School of Mathematics and Physics,Lanzhou Jiaotong University,Lanzhou 730070,China)
出处
《贵州大学学报（自然科学版）》
2021年第2期57-60,共4页
Journal of Guizhou University:Natural Sciences
基金
国家自然科学基金资助项目(61663018)。
