Community Evolutional Network for Situation Awareness Using Social Media

IEEE Access

Kai Hu¹  Mingxuan Dou²  Mengmeng Li²  Mengling Qiao²  Xiaokang Fu²  Yandong Wang² 

[1] Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi, China;State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China;

关键词: Co-word network;    community evolution;    topic evolution;    situational awareness;   

DOI  :  10.1109/ACCESS.2020.2976108

来源: DOAJ

【 摘 要 】

Social media is important for situational awareness during a disaster. During a disaster, the situation of emergence often changes over time and hence the topics of social media messages generated by social media users also change accordingly. Few studies quantitatively describe the topic evolution of social media during a disaster and the corresponding relationship between topic evolution and disaster process. We address this problem using co-word network analysis and present a new method based on the community evolution of the co-word network to analyze topic evolution over time in social media. The method uses communities of the co-word network in social media to represent topics. Based on the theory of community evolution, a community evolutional network is proposed to support and quantify the evolution of the topics. We implemented the proposed method in a case study, “July 2012 Beijing flood” using the Sina Weibo dataset. Results show that our method can well quantify the evolution process of topics and validate the effectiveness of our method in real-world applications. The method can facilitate the understanding of public expression dynamics during a disaster and be used to reveal the process and stages of a disaster.

【 授权许可】

Unknown