摘要
移动互联网的快速发展,方便了人们在网络上评述事情、表达观点的同时,也在网络空间中留下了能够反映个体在现实空间中行为的大量电子足迹数据。可以说,保存在网络空间中的电子足迹数据隐藏着个体在现实世界中的心态和情感秘密。那么,如何挖掘出隐藏在这些评论中的有用信息,给有关部门提供情报服务则显得很有必要。然而,尽管有一些基于网络评论数据进行情感分析的研究,但很少有人能够进一步深入并归类差评所折射出的现实空间中的具体问题而进行分析。本文主要爬取“去哪儿网”上相关于青海旅游的评论数据重点进行分析。利用Python中的Jieba对评论分词,通过SnowNLP模块计算情感极性,以此判断游客对景点的情感倾向性。通过分析得出游客在青旅游期间的情感态势。然后,对负向情感较集中的评论内容归类统计,分析差评所折射出来的在现实世界中引起人们不满意的那些问题。同时,结合实测调研数据进行比对,形成意见报告,为旅游主管部门在景点管理与下一步的规划建设中提供服务。
The rapid development of mobile Internet not only facilitates people to comment on events and express views on the net⁃work,but also a large number of electronic footprint data are left in cyberspace that can reflect the behavior of individuals in real world.It can be said that the electronic footprint data stored in cyberspace hided the individual's mental and emotional secrets in the real space.Therefore,it is necessary to dig the useful information hidden in these comments and provide intelligence services to the relevant departments.However,although there are some studies based on online comment data for emotional analysis,few people can further deepen and categorize the specific problems in the real world reflected by the bad comments.This paper mainly analyzes the data of the tourism-related comments for Qinghai Province.Using the Jieba to analyze these comments,calculating emotional polarity through snowNLP Module in Python,so as to judge the emotional tendency of the tourists to the scenic spots.Through the analysis,we get the emotional situation of tourists during the tourism in Qinghai.Then,the content of the negative emo⁃tion is statistically classified,and the problems that people are not satisfied in the real world,which are reflected by the bad com⁃ments,are analyzed.At the same time,combined with the actual survey data to form the opinion report,and providing services to the tourism department for the scenic area management.
作者
唐明虎
Tang Ming-hu(Qinghai Nationalities University,Xining 810007,China)
出处
《电脑知识与技术》
2020年第20期23-27,31,共6页
Computer Knowledge and Technology
基金
青海省应用基础研究项目“多层异质复杂网络的链路预测研究及其在青海旅游景点自动推荐中的应用”(2018-ZJ-707)
教育部“春晖计划”合作科研项目“耦合多元信息属性关系的多层异质复杂网络链路预测研究”的研究成果之一。项目负责人:唐明虎。
关键词
旅游
网络评论
情感分析
大数据
景区管理
travel
network comments
sentiment analysis
big data
scenic area planning
