中文    English

Journal of Library and Information Science in Agriculture ›› 2023, Vol. 35 ›› Issue (11): 86-97.doi: 10.13998/j.cnki.issn1002-1248.23-0812

Previous Articles     Next Articles

Analysis of Information Dissemination of Emergencies Based on Weibo User Characteristics

LI Sijia1, ZHENG Deming1, SUN Zhengyi2   

  1. 1. Research Center for Network Public Opinion Governance, China People's Police University, Langfang 065000;
    2. Public Security Detachment of Tongzhou Branch of Beijing Municipal Public Security Bureau, Beijing 101100
  • Received:2023-09-27 Online:2023-11-05 Published:2024-02-28

Abstract: [Purpose/Significance] With the popularity and development of social media, Weibo has become an important information transmission platform. Understanding the law of emergency information transmission based on the characteristics of Weibo users is of great significance for grasping the development trend of events, evaluating the influence of information, and formulating effective response strategies. [Methods/Process] Selecting typical cases of four types of emergencies (natural disasters, accidents, public health events, and social security events) as the research objects, this paper crawled the user data of the information transmission on the Weibo platform and analyzed the distributions of user gender, user geographical distribution, user attention and fan number and user type of the information transmission for these events, in order to reveal the differences and similarities of the user characteristics and transmission laws for the four types of emergencies. [Results/Conclusions] As for the similarities of the user characteristics and transmission laws, first, the audiences of the four types of emergencies have obvious regional characteristics, and the users in economically developed provinces generally have a higher attention rate. Second, the transmission users of all types of emergencies are generally concentrated on active users and grassroot users with strong and weak propagation power respectively, accompanied by a small number of authoritative users with strong influence. However, there are differences in the broadness and gender distribution of the audiences for different types of emergencies. First, natural disasters have a wider spread of the audiences and relatively higher attentiveness; accidents and public health events tend to be local events with relatively low attentiveness, whose audiences may be more concentrated in and around the affected areas; the audience spread of social security events is scattered depending on the nature of the event, the scope of influence as well as the communication channels. Second, female users pay more attention to natural disasters, public health events and social security events, while male users pay more attention to accidents, which can be attributed to the different emotional orientations and psychological characteristics associated with users of different genders. These results provide insights for the formulation of targeted guidance strategies for information dissemination. In future studies, we will collect data on other social media platforms, obtain more information on user characteristics through different channels, and introduce more in-depth analysis methods and indicators to comprehensively reveal the dynamic mechanisms of emergency information dissemination, thus improving the accuracy and effectiveness of the research.

Key words: social media, Weibo, information dissemination, user characteristics, emergency

CLC Number: 

  • TP391
[1] 王宏. “突发事件”概念的界定与探讨[J]. 淮海工学院学报(人文社会科学版), 2013, 11(24): 9-11.
WANG H.An analysis of the definition of "emergency"[J]. Journal of Huaihai institute of technology(humanities & social sciences edition), 2013, 11(24): 9-11.
[2] 耿晨皓, 王胜本, 郝翔宇, 等. 高校公共卫生突发事件治理:概念界定、现状分析和应对路径[J]. 华北理工大学学报(社会科学版), 2022, 22(6): 49-54.
GENG C H, WANG S B, HAO X Y, et al.Governance of public health emergencies in colleges and universities: Concept definition, status analysis and response paths[J]. Journal of North China university of science and technology (social science edition), 2022, 22(6): 49-54.
[3] 王世雄, 朱明旻, 骆彦余. 信息疫情中真假信息竞争性传播研究[J]. 现代情报, 2023, 43(9): 124-136.
WANG S X, ZHU M M, LUO Y Y.Competitive propagation between true and false information in the context of infodemic[J]. Journal of modern information, 2023, 43(9): 124-136.
[4] 杨妺, 王妍, 王传彪, 等. 突发事件网络的传播规律及特征——以知网事件为例[J]. 中国传媒大学学报(自然科学版), 2022, 29(6): 58-67.
YANG M, WANG Y, WANG C B, et al.Network propagation law and characteristics of emergencies-Take the CNKI incident as an example[J]. Journal of communication university of China(science and technology), 2022, 29(6): 58-67.
[5] 王莉, 刘庆彰. 突发公共事件网络舆情传播路径演变研究[J]. 现代工业经济和信息化, 2016, 6(3): 97-99.
WANG L, LIU Q Z.Analysis on propagation evolution of network public opinion for unexpected emergency[J]. Modern industrial economy and informationization, 2016, 6(3): 97-99.
[6] 陈迎欣, 苏泽伟, 周蕾. 灾害救助信息网络传播的关键因素及有效路径[J]. 情报杂志, 2022, 41(5): 106-111.
CHEN Y X, SU Z W, ZHOU L.Key factors and effective path of disaster relief information network dissemination[J]. Journal of intelligence, 2022, 41(5): 106-111.
[7] 王林, 王可, 吴江. 社交媒体中突发公共卫生事件舆情传播与演变——以2018年疫苗事件为例[J]. 数据分析与知识发现, 2019, 3(4): 42-52.
WANG L, WANG K, WU J.Public opinion propagation and evolution of public health emergencies in social media era: A case study of 2018 vaccine event[J]. Data analysis and knowledge discovery, 2019, 3(4): 42-52.
[8] 任景华. 突发事件中微博信息的传播及其思考——基于“福建漳州PX项目爆炸事件” 的实证分析[J]. 社会科学家, 2016(8): 53-55.
REN J H.Weibo's information dissemination in emergencies and its thinking-Based on the empirical analysis of "PX project explosion in Zhangzhou, Fujian"[J]. Social scientist, 2016(8): 53-55.
[9] 黄君婷, 叶文举. 突发事件中政务微博的舆情信息工作策略研究——以“9·5”泸定地震为例[J]. 秘书, 2023(4): 81-92.
HUANG J T, YE W J.Strategy of governmental micro-blog's public opinions work in emergency-A case study of "9·5" Luding earthquake[J]. Secretary, 2023(4): 81-92.
[10] 张宇, 王建成. 突发事件中政府信息发布机制存在的问题及对策研究——基于2015年“上海外滩踩踏事件” 的案例研究[J]. 情报杂志, 2015, 34(5): 111-117, 65.
ZHANG Y, WANG J C.On the problems and countermeasures of government information release mechanism in emergency-Based on the case study of 2015 Shanghai bund stampede incident[J]. Journal of intelligence, 2015, 34(5): 111-117, 65.
[11] 张海波, 童星. 中国应急管理结构变化及其理论概化[J]. 中国社会科学, 2015(3): 58-84, 206.
ZHANG H B, TONG X.Changes in the structure of emergency management in China and a theoretical generalization[J]. Social sciences in China, 2015(3): 58-84, 206.
[12] 欧阳桃花, 郑舒文, 程杨. 构建重大突发公共卫生事件治理体系:基于中国情景的案例研究[J]. 管理世界, 2020, 36(8): 19-32.
OUYANG T H, ZHENG S W, CHENG Y.The construction of a governance system for large-scale public health emergency: A case study based on the Chinese scenario[J]. Management world, 2020, 36(8): 19-32.
[1] JIANG Zhihui, LI Xuan, CAO Gaohui. Causes and Influence Paths of Digital Stress among Social Media Users [J]. Journal of Library and Information Science in Agriculture, 2023, 35(11): 64-76.
[2] CHAI Xuefei, XING Fei. Health Information Needs and Service of the Elderly Under Major Public Health Emergencies [J]. Journal of Library and Information Science in Agriculture, 2023, 35(1): 99-107.
[3] ZHAO Youlin, CAO Hongnan. Government Microblog Information Exchange Efficiency and Its Influencing Factors for Emergency Management [J]. Journal of Library and Information Science in Agriculture, 2022, 34(9): 72-85.
[4] KE Tingjuan, ZENG Zhen. Problems and Influencing Factors of Rural Information Dissemination under Different Themes [J]. Journal of Library and Information Science in Agriculture, 2022, 34(7): 14-26.
[5] SONG Kai, RAN Congjing. Digital Technologies Aid Intelligent Epidemic Prevention and Control: Community-based Rapid Detection and Tracking Platform of COVID-19 [J]. Journal of Library and Information Science in Agriculture, 2022, 34(5): 92-101.
[6] LYU Kun, CHEN Yaoyao, XIANG Minhao. Influencing Factors of Sina Weibo Information Service Quality from the Perspective of Users: Exploratory Analysis Based on Grounded Theory [J]. Journal of Library and Information Science in Agriculture, 2022, 34(10): 70-81.
[7] ZHAO Xueqin, YANG Yifan. Analysis of Public Emergency Information Search Behavior and Research on Service Strategy Under Financial Emergencies [J]. Journal of Library and Information Science in Agriculture, 2022, 34(1): 74-85.
[8] XING Yunfei, LI Yuhai. Visualization of Topic Graph of Weibo Public Opinion Based on Text Mining [J]. Journal of Library and Information Science in Agriculture, 2021, 33(7): 12-23.
[9] YIN Hongmiao. A Survey on Online Services for Children in Public Libraries in China under the Background of Public Health Emergencies [J]. Journal of Library and Information Science in Agriculture, 2021, 33(1): 62-72.
[10] MU Di, CHEN An. Multi-dimensional intelligence model for public health emergencies and its application [J]. Journal of Library and Information Science in Agriculture, 2020, 32(4): 15-22.
[11] LI Yan. The Research of Information Behavior on Wechat Community——Based on Information Grounds [J]. Agricultural Library and Information, 2019, 31(3): 56-64.
[12] FENG Li. Sentiment Analysis and Feature Extraction of Weibo Short Text [J]. , 2018, 30(9): 56-60.
[13] ZHU Miao, CHEN Juan. Analysis on Networking, Digitalization and New Media Application of Journals of Agricultural Universities in China [J]. , 2018, 30(5): 126-131.
[14] HU Anqi. Research on Enterprise Competitive Intelligence Analysis Model Based on Social Media User Comments [J]. , 2018, 30(4): 46-51.
[15] REN Wei. The Application Status and Countermeasure Study of Social Media Platform in University Library [J]. , 2018, 30(4): 101-105.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!