摘要
为了对疫情期间口罩的用户评论数据进行情感关注分析,本文用谷歌浏览器的插件Web Scraper爬取了2020年3月1日到4月11日中淘宝网的口罩的共计143330条用户购买评论数据.为了提高情感预测的精度,在此数据集上经过人工标注情感为积极和消极的共计14400条数据后,用SnowNLP情感分析模型进行了训练,最后用训练后的语料库进行了情感预测.从整体上可见用户评论的情感是积极的.在用户评论的每日情感变化趋势上,本土新增病例(不含海外输入)的趋势在一定程度上影响着用户每日情感趋势的整体变化,而国内新增病例(含海外输入)的局部波动变化趋势也影响着每日情感局部的相应波动变化趋势.在对预测后的评论进行分类后,发现用户的积极评论中对口罩的关注主要集中在口罩的质量、包装、价格、厚实,而在消极的评论中对口罩的关注主要集中在质量、包装、味道和是否为医用.
In order to analyze the sentimental focus of the comment data from users of masks during the outbreak of virus,we extracted 143330 comments about the purchase from Taobao users from March 1 st to April 11 th,2020 by means of the Web Scraper of Google browser.To improve the accuracy of the sentimental estimation,each comment of the total14400 pieces was manually marked as positive or negative emotion on this data set.And then we used SnowNLP,the sentimental analysis model to train them.At last,the trained corpus was used for sentimental estimation.The overall sentiment of the comments was proved positive.On the basis of the daily emotional variation trend of users’comments,the trend of local new cases(excluding overseas input)to some extent affects the overall change of their daily emotional trend.And the local fluctuation trend of domestic new cases(including overseas input)also affects that of the everyday emotional performance.After classifying the predicted comments,we found that users’positive comments focused on the quality,packaging,price,and thickness of masks,while negative comments focused on the quality,packaging,smell,and whether the masks were for medical use.
作者
曾志伟
刁明光
王欣鹏
何炳辉
ZENG Zhi-Wei;DIAO Ming-Guang;WANG Xin-Peng;HE Bing-Hui(School of Information Engineering,China University of Geosciences(Beijing),Beijing 100083,China)
出处
《计算机系统应用》
2020年第12期263-267,共5页
Computer Systems & Applications
基金
2019大学生创新创业训练计划项目A(X201911415126)
