沙海潮1，冯 钧1，杭婷婷1，成建国2

(1. 河海大学计算机与信息学院，江苏 南京 210098;2. 水利部信息中心，北京 100053)

　　摘 要：针对突发水事件的各类数据信息对分析事件起因、发展和后续影响有着相当重要的价值。在研究应用现状分析的基础上，利用事件热度与Bi-Lstm情感分析2个模型，对2021年嘉陵江铊污染突发事件进行分析，分析结果说明：事件热度方面，华东、西北地区的公众较为活跃，微博热度具有聚集性和滞后性的特点，新闻平台则体现出热度的延续性特点;事件舆情方面，微博舆情表现出比新闻平台舆情更为负面的情绪，两者都缺乏相对理性客观的评论。从后续影响角度看，部分气象水文因素导致铊污染二次发生，其次疫情前后，炼钢、冶锌行业利润存在大幅度波动态势，产量受高利润驱动而提高，一定程度诱发此类污染事件。突发涉水事件舆情传播迅速，影响范围较广，事件发展程度与舆情走势息息相关。

　　关键词：突发水事件;舆情;大数据分析;情感分析;事件热度分析;后续影响

　　Analysis on public sentiment and subsequent impact of water-related emergency——A case study of thallium pollution in Jialing River

　　SHA Haichao1, FENG Jun1, HANG Tingting1, CHENG Jianguo2

　　(1. College of Computer and Information, Hohai University, Nanjing 210098, China;

　　2. Information Center, Ministry of Water Resources, Beijing 100053, China)

　　Abstract: All kinds of data and information for water-related emergencies are of great value to analyze the cause, development and impact of the events. Based on the analysis of the research and application status, the event heat model and Bi-LSTM sentiment analysis model are used to comprehensively analyze the Jialing River thallium pollution emergency in 2021. Results show that: in terms of event popularity, the public in East China and Northwest China are more active, the popularity of microblog has the characteristics of aggregation and lag, and the news platform reflects the continuity of the popularity. In terms of event public opinion, microblog public opinion shows more negative emotions than news platform public opinion, both of which lack relatively rational and objective comments. From the perspective of the follow-up impact of public opinion, some meteorological and hydrological factors lead to the secondary occurrence of thallium pollution. Before and after the epidemic, the profits of steel-making and zinc smelting industries are fluctuated greatly, and the output is driven by high profits, which, in a certain degree, induces such pollution events. Public opinion of sudden water-related incidents spreads rapidly and has a wide range of influence. The development degree of incidents is closely related to the trend of public opinion.

　　Key words: water-related emergency; public opinion; big data analysis; sentiment analysis; event heat analysis;subsequent impact