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高校网络舆情行为影响因素分析——以江西高校为例
引用本文:彭泰中,廖冰,廖文梅,叶小华.高校网络舆情行为影响因素分析——以江西高校为例[J].江西农业大学学报(社会科学版),2013(4):577-582.
作者姓名:彭泰中  廖冰  廖文梅  叶小华
作者单位:[1]江西农业大学计算机信息与工程学院,江西南昌330045 [2]江西农业大学经济管理学院,江西南昌330045
基金项目:江西省高校人文社科研究项目(MKSl015)
摘    要:目前,高校网络舆情行为已经进入全面发展时期,正确引导网络舆情发展显得尤为重要。利用Logistic回归模型对高校网络舆情行为与各个自变量进行回归分析,模型结果表明,性别、出生地、性格、政治面貌、上网时间、家庭成员、专业类型、感兴趣程度、发泄情绪频率、情感因素、事件话题热度在不同程度上、不同方向上影响高校网络舆情行为。建议通过建立公开透明、及时有效的学校信息发布、培养网络论坛的"意见领袖"、提高网络道德等引导高校网络舆情。

关 键 词:网络舆情  影响因素  Logistic回归模型

The Analysis on the Influent Factors of the Behavior on Network Public Opinion In Colleges A Case of Jiangxi Colleges
PENG Tai-zhong,LIAO Bing,LIAO Wen-mei.,YE Xiao-hua.The Analysis on the Influent Factors of the Behavior on Network Public Opinion In Colleges A Case of Jiangxi Colleges[J].Journal of Jianxi Agricultural University :Social Sciences Edition,2013(4):577-582.
Authors:PENG Tai-zhong  LIAO Bing  LIAO Wen-mei  YE Xiao-hua
Institution:1.College of Information and Engineering, Jiangxi Agriculture University, Nanchang 330045, China; 2. College of Economics and Management,Jiangxi Agricultural University, Nanchang 330045, China)
Abstract:At present,behavior on network public opinion of the college has being into a period of compre- hensive development.It is particularly important to properly guide the behavior of the network public opinion.The article had a regression analysis on behavior of the college network public opinion and various independent varia- bles with the Logistic regression method.The model results showed that gender, birth place, character, political af- filiation, online time, family members, professional type,interest degree, emotion, affeetive factors, event topic heat degree had an effect on college network public opinion behavior in different degree, in different direction.The ar- ticle described the guiding ways of improving college network public opinion from the establishment of an open and transparent,timely and effective school information, develop network forum" opinion leaders" and the im- provement of the network morality.
Keywords:network public opinion  influent factors  Logistic regression analysis
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