四川省科技厅新型冠状病毒疫情防控科技攻关项目（2020YFS0007）； 四川大学新冠肺炎应急项目（2020scunCoV应急20012）； 四川大学大学生创新创业计划（C2020109217）
Relying on 60 thousand blogs and 15 thousand hot blog reviews in Sina micro-blog from January 1st to February 29th in 2020, this article launches the analysis of the public opinion to the topic about novel coronavirus pneumonia based on distributed crawler technology, distributed database system, SnowNLP sentiment analysis model and K-Means algorithm. This analysis can show visually the spatial and temporal evolution process of Internet public opinion in the events of this epidemic situation. On spatial dimension, the netizens' attitude towards this pneumonia epidemic has roughly gone through three periods. The first period appears in the shape of bigger fluctuation which presents as tension and anxiety. The second period appears in the shape of rising slowly which presents as unity and excitement. The third period appears in the shape of slight fluctuation which presents as confidence and stability. On the whole, it shows the emotional state that positive is greater than negative and Optimism is greater than pessimism. On spatial dimension, we find that the area which has the most serious epidemic has the most comments and the lowest emotional value through geographical statistical analysis.
引用本文格式： 陈兴蜀,常天祐,王海舟,赵志龙,张杰. 基于微博数据的“新冠肺炎疫情”舆情演化时空分析[J]. 四川大学学报: 自然科学版, 2020, 57: 409.复制