摘要
[目的/意义]在网络社交媒体平台上,不同的公众情感在信息交互和传播过程中往往会出现“相生相克”现象,准确掌握和预测社交媒体环境中公众情感热度的变化规律,对于正确引导突发事件的网络舆情具有重要的理论价值。[方法/过程]在定性分析网民情感特征和交互模式基础上,结合生态科学中种群共生理论和Logistic方程,构建公众情感共生模型(E-SM),通过定义共生系数划分情感的7种共生模式,可使用差分回归法计算情感共生系数和模型稳定点,进而确定网络舆情中公众情感的共生模式和预测趋势。[结果/结论]通过共生模式的仿真模拟得出稳定状态下的公众情感值和增长速度与情感饱和量、共生系数、固有增长率、情感初值间的关系,以及7种情感共生模式的特点,并根据新浪微热点统计的微博热门话题事件中公众情感的真实数据与差分方程进行拟合,验证了E-SM模型具有很高的准确性。
[Purpose/significance]On the network social media platform,different public emotions tend to“generate and overcome each other”in the process of information interaction and communication.Accurately mastering and predicting the change law of public emotion heat in the social media environment has important theoretical value for correctly guiding the network public opinion of emergencies.[Method/process]Based on the qualitative analysis of Internet users’emotional characteristics and interaction modes,combined with the population symbiosis theory and Logistic equation in ecological science,the public emotional symbiosis model(E-SM)is constructed.Seven symbiosis modes of emotion are divided by defining symbiosis coefficient,and the differential regression method can be used to calculate the emotional symbiosis coefficient and model stability point,Then determine the symbiotic model and prediction trend of public emotion in network public opinion.[Result/conclusion]Through simulation,the relationship between public emotion value and growth rate in steady state and emotion saturation,symbiosis coefficient,inherent growth rate and initial emotion value,as well as the characteristics of seven emotion symbiosis modes are obtained.Finally,according to Sina Mdata’s statistics,the real data of public emotion in Sina Weibo hot topic events are fitted with the difference equation to verify the high accuracy of the E-SM model.
出处
《情报理论与实践》
CSSCI
北大核心
2022年第7期148-157,共10页
Information Studies:Theory & Application
基金
河北省高等学校人文社会科学研究项目“基于舆情大数据的群体性事件感知与应对策略研究”(项目编号:BJ2020210)
警察大学科研重点专项课题“人工智能背景下网络虚假信息识别与治理对策研究”(项目编号:ZDZX202201)
教育部人文社会科学项目“基于舆情大数据的突发事件网民情感风险感知与治理研究”(项目编号:20YJC630145)的成果之一。
关键词
网络舆情
情感预测
LOGISTIC方程
共生模式
差分回归
情感共生
network public opinion
emotion prediction
logistic equation
symbiotic model
differential regression
emotional symbiosis
