网络舆情态势及情感多维特征分析与可视化——以COVID-19疫情为例

2020年初,新型冠状病毒肺炎（COVID-19）疫情席卷全国,疫情发展变化引发了社会各界的广泛关注。社交媒体平台作为网络舆情的重要载体,如何从中全面、准确挖掘分析网络舆情特征是疫情防控过程中的重要问题。本研究首先从舆情本体与客体时空关联的角度构建了疫情期间网络舆情多维分析模型,获取了2020年1月17日—3月17日多个媒体平台中新冠肺炎疫情相关的网络舆情数据;其次以疫情蔓延的视角,运用比较研究法、Spearman相关系数等方法探索了武汉市、湖北省及全国尺度下的网络舆情态势时空演变及语义特征;最后使用HowNet情感词典和情感词汇本体进行了舆情情感分析,并使用可交互信息图表对其进行可视化。结果表明：① 武汉市、湖北省、全国尺度下的每日舆情数据数量与每日新增病例数之间存在正相关关系;② 舆情数据数量的空间分布与疫情分布存在正相关关系,舆情数据数量多的地区多为疫情较为严重的地区; ③ 研究时段内不同媒体平台的舆情中立情感最多,新闻平台与论坛、微信、微博相比,整体情绪更为正面;④ 在疫情发展的不同阶段,微博热搜数据情感特征有较大差异,总体上呈现正面情绪多于负面。研究表明,基于本文提出的多维分析模型可以直观展现疫情期间多尺度下的舆情态势、舆情焦点和情绪变化,从而为政府及相关部门有效引导与控制网络舆情提供理论基础支撑和参考借鉴。

Analysis and Visualization of Multi-dimensional Characteristics of Network Public Opinion Situation and Sentiment:Taking COVID-19 Epidemic as an Example

At the beginning of 2020, COVID-19 epidemic swept across China, and the development of COVID-19 attracted extensive attention from all sectors of society. Social media platform is an important carrier of online public opinion. In the process of epidemic prevention and control, it is very important to analyze the characteristics of network public opinion comprehensively and accurately. Firstly, from the perspective of spatiotemporal correlation between public opinion ontology and object, we construct a multi-dimensional analysis model of network public opinion during the epidemic period. We obtained the network public opinion data related to the covid-19 epidemic in multiple media platforms from January 17 to March 17, 2020. Secondly,from the perspective of epidemic spread, the spatial and temporal evolution and semantic characteristics of network public opinion in Wuhan, Hubei and the national scale are explored by comparative study and Spearman correlation coefficient. Finally, we use HowNet sentiment dictionary and emotional vocabulary ontology to analyze public opinion sentiment, and use interactive information chart to visualize the above results. The results show that:(1) The characteristics of time changes of public opinions are basically the same in Wuhan, Hubei province and China. There is a positive correlation between the number of daily public opinions and the number of new cases per day. With the rapid spread of the epidemic, the number of daily public opinions continues to increase. As the epidemic is gradually brought under control, the number of daily public opinions has shown a tortuous downward trend.(2) There is a positive correlation between the spatial distribution of public opinion data and the distribution of epidemic situation. The spatial distribution of the number of public opinions is similar to the distribution of the epidemic situation, and the areas with a large number of public opinions are mostly areas with severe epidemics. Changes in public opinions are spatially related to the development of the epidemic.(3) During the epidemic, the neutral sentiment of online public opinions was the most. Compared with forums, We Chat and Weibo, news platforms have a more positive overall sentiment.(4) At different stages of the development of the epidemic, the emotional characteristics of Weibo hot search data are quite different. The mood changed from anxiety in the early stage of the epidemic to excitement in the mid-term. And as the epidemic is gradually brought under control, emotions have also stabilized. Generally speaking, there are more positive emotions than negative emotions. Research shows that the multi-dimensional analysis model proposed in this article can visually show the public opinions situation, public opinions focus, and emotional changes at multiple scales during the epidemic.