微博用户对剩男剩女的社会态度研究——基于微博文本情感倾向分析
The Micro-Blog Users’ Social Attitude towards Leftover Men and Women Based on the Text Sentiment Analysis
DOI: 10.12677/ASS.2015.42016, PDF, HTML, XML,  被引量 下载: 2,900  浏览: 11,029  科研立项经费支持
作者: 张 雪, 王 鹏:山东师范大学心理学院,山东 济南
关键词: 剩男剩女社会态度微博文本中文分词情感倾向分析Leftover Men and Women Attitude Micro-Blog Messages Chinese word segmentation Analysis of Emotional Tendency
摘要: 本研究探讨了网络用户对剩男剩女的社会态度。采用微博文本情感倾向分析的方法对1000条新浪原创微博进行态度研究。采用微博文本情感倾向分析的方法对1000条新浪原创微博进行态度研究,其结果显示微博用户对剩男剩女群体持负向态度。另对标签为剩男剩女的60名新浪微博用户近期发表的900条原创微博进行情感倾向性分析,发现剩男剩女群体的微博呈中性态度,且剩男和剩女的微博关注话题存在明显性别差异。本研究结果对于社会正确理性看待逐渐增多的剩男剩女具有一定的启示意义,对剩男剩女在择偶问题上树立正确择偶观具有引导作用。
Abstract: This study investigated the Internet users’ social attitude towards leftover males and females. Re-lated to the topic of leftover males and females, 1000 original micro-blog messages selected from Sina Weibo were used to identify the emotional tendencies of these messages. The results showed that the micro-blog users held negative attitude towards leftover males and females. In addition, the emotional tendencies of the 900 original micro-blog messages that were recently published from 60 Sina Weibo users who were marked by leftover males or females were analyzed as well. The results showed that the emotional tendencies of these messages were neutral. Besides, there were dramatically differences on the topics focused by leftover males and females. The research not only induces a rational social attitude towards leftover males and females, but also plays a guiding role for them in setting up the correct conception on choosing spouse.
文章引用:张雪, 王鹏. 微博用户对剩男剩女的社会态度研究——基于微博文本情感倾向分析[J]. 社会科学前沿, 2015, 4(2): 98-106. http://dx.doi.org/10.12677/ASS.2015.42016

参考文献

[1] 雪杉 (2010) 剩男剩女现象对社会的影响不容忽视. 东北之窗, 20-21.
[2] 网易科技 (2014) 第33次中国互联网络发展状况统计报告. http://www.199it.com/archives/187745.html
[3] 杜伟夫 (2010) 文本倾向性分析中的情感词典构建技术研究. 博士学位论文, 哈尔滨工业大学, 哈尔滨, 3-4.
[4] 王洪伟, 刘勰, 尹裴, 廖雅国 (2010) Web文本情感分类研究综述. 情报学报, 5, 931-932.
[5] 孙铁利, 刘延吉 (2009) 中文分词技术的研究现状与困难. 信息技术, 7, 187-189.
[6] 张华平 (2014) NLPIR汉语分词系统. NLPIR简介. http://ictclas.nlpir.org/
[7] Tagxedo (2014) 词云技术. Tagxedo-Creator. http://www.tagxedo.com
[8] CNKI (2007) 知网(HowNet). HowNet’s Home Page. http://www.keenage.com
[9] 陈晓东 (2012) 基于情感词典的中文微博情感倾向分析研究. 硕士学位论文, 华中科技大学, 武汉, 21-23.
[10] 佘伟成 (2013) 基于微博的热点发现与情感倾向分析. 硕士学位论文, 云南大学, 昆明, 40-41.
[11] Scanzoni, J. and Fox, G.L. (1980) Sex roles, family and society: The seventies and beyond. Journal of Marriage and the Family, 42, 743-756.
[12] 王彬 (2012) 从经济学视角分析“剩女”现象. 中国青年研究, 6, 81.