基于SVM和CRF的三孩政策舆情省份差异分析

Analyzing Public Opinion on Three-Child-Policy with Sentiment Classification and Keyword Extraction

【目的】对三孩政策相关舆情在不同省份的区别进行分析研究。【应用背景】三孩政策舆情的分析往往将全网的三孩舆情视为一个整体,忽视了不同省份群体对三孩政策的诉求、关注点的不同;对三孩政策舆情的文本研究存在方法简单、数据来源单一的问题。【方法】首先从统计学角度基于时间序列分析三孩舆情热度,然后基于支持向量机方法对三孩舆情进行情感分析,发现负面舆情,进而基于CRF方法进行关键词提取并形成词云。对不同省份的三孩舆情文本展开研究,得到不同省份的三孩负面舆情词云。对比不同省份负面舆情关键词与不同省份的政治、经济统计数据,分析其中的联系。【结果】三孩政策舆情热度高于同期政策类舆情。舆情以中性情感为主,占60.56%;积极情感为辅,占35.15%;存在少量负面舆情,占4.29%。不同省份的舆情关注点不同,这些差别与各省的政治经济生态差异是有关联性的。【结论】三孩政策的舆情工作应当考虑不同省份的实际情况,针对人民关切的问题做出回应,及时跟进相关的配套措施。

[Objective]This paper studies the public opinion on the three-child-policy in different Chinese provinces.[Context]Existing research on this issue addresses public opinion from the Web as a whole,and ignores the demands or concerns from individual province.These studies’research methods are rather simple with single data source.[Methods]Firstly,we analyzed the public opinion on three-child-policy with time series method from the statistical perspective.Then,we examined their sentiments with the SVM model,and extracted keywords from the negative opinion with the CRF model.Third,we created word clouds for these keywords.Finally,we conducted research on these public opinion in different provinces and generated word clouds for them.We also examined the ties between political or economic statistics and the negative key words from different provinces.[Results]The three-child-policy was more popular than other policies during the same period.The public opinion was dominated by neutral sentiments(60.56%),followed by the positive(35.15%)and the negative ones(4.29%).Public concerns in different provinces were different and correlated to the political,economic and ecological factors.[Conclusions]Different provinces should adopt customized public opinion guidance to support the three-child-policy,which will address people’s concerns more effectively.