Zena Tian;Guijuan Zhang;Hui Yu;Hong Liu;Dianjie Lu
{"title":"NegEmotion: Explore the Double-Edged Sword Effect of Negative Emotion on Crowd Evacuation","authors":"Zena Tian;Guijuan Zhang;Hui Yu;Hong Liu;Dianjie Lu","doi":"10.1109/TCSS.2023.3344172","DOIUrl":null,"url":null,"abstract":"In emergencies, negative emotion has a significant impact on decision-making during crowd evacuation. Psychological studies suggest that negative emotion in decision-making has a double-edged sword effect. Excessive negative emotion has adverse impacts, such as causing crowd chaos and congestion. Conversely, moderate negative emotion has a positive effect by speeding up crowd movement. However, current researches mainly focus on one aspect which is how to reduce the negative effects of negative emotion on crowd evacuation, while overlooking the benefits of negative emotion. How to fully explore the double-edged sword effect of negative emotion and regulate negative emotion to improve the efficiency of crowd evacuation is still an open issue. To achieve this, we propose the NegEmotion model which considers the positive impact of negative emotion on crowd evacuation, and regulates crowd emotion by controlling knowledge spreading according to Siminov's psychological principle. In this model, the knowledge spreading network (KSN) and the stress emotional contagion network (SECN) are constructed. Based on these networks, we study the evolution process of knowledge spreading and stress emotional contagion, respectively. Next, we formulate the emotional regulation as an optimization problem to maximize the efficiency of crowd evacuation. Then, a heuristic algorithm is used to solve for the optimal emotional regulation strategy. Finally, a crowd simulation system is implemented to verify the effectiveness of our NegEmotion model. The experimental results show that our method is effective to improve the efficiency of crowd evacuation.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10387507/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 0
Abstract
In emergencies, negative emotion has a significant impact on decision-making during crowd evacuation. Psychological studies suggest that negative emotion in decision-making has a double-edged sword effect. Excessive negative emotion has adverse impacts, such as causing crowd chaos and congestion. Conversely, moderate negative emotion has a positive effect by speeding up crowd movement. However, current researches mainly focus on one aspect which is how to reduce the negative effects of negative emotion on crowd evacuation, while overlooking the benefits of negative emotion. How to fully explore the double-edged sword effect of negative emotion and regulate negative emotion to improve the efficiency of crowd evacuation is still an open issue. To achieve this, we propose the NegEmotion model which considers the positive impact of negative emotion on crowd evacuation, and regulates crowd emotion by controlling knowledge spreading according to Siminov's psychological principle. In this model, the knowledge spreading network (KSN) and the stress emotional contagion network (SECN) are constructed. Based on these networks, we study the evolution process of knowledge spreading and stress emotional contagion, respectively. Next, we formulate the emotional regulation as an optimization problem to maximize the efficiency of crowd evacuation. Then, a heuristic algorithm is used to solve for the optimal emotional regulation strategy. Finally, a crowd simulation system is implemented to verify the effectiveness of our NegEmotion model. The experimental results show that our method is effective to improve the efficiency of crowd evacuation.
期刊介绍：
IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.
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