An approach for emotions and behavior modeling in a crowd in the presence of rare events. (December 2016)

• Record Type: Journal Article
• Authors: Saifi, Lynda; Boubetra, Abdelhak; Nouioua, Farid
• Is Part Of: Adaptive behavior. Volume 24:Number 6(2016)
• Page Start: 428
• Page End: 445
• Publication Date: 2016-12
• Subjects: Crowd -- emotion -- critical emotions -- personality -- behavior -- influence -- emotional influence -- behavioral influence; Animal behavior -- Periodicals; Animals -- Adaptation -- Periodicals; Adaptability (Psychology) -- Periodicals; Adaptation, Psychological -- Periodicals; Artificial intelligence -- Periodicals; 591.5
• DOI: 10.1177/1059712316674784
• Languages: English
• ISSNs: 1741-2633

Abstract

A common phenomenon in everyday life is that, when a strange event occurs or is announced, a regular crowd can completely change, showing different intense emotions and sometimes uncontrollable and violent emerging behavior. These emotions and behaviors that disturb the organization of a crowd are of concern in our study, and we attempt to predict these suspicious circumstances and provide help in making the right decisions at the right time. Furthermore, most of the models that address crowd disasters belong to the physical or the cognitive approaches. They study pedestrian flow and collision avoidance, etc., and they use walking speed and angle of vision. However, in this work, based on a behavioral rules approach, we aim to model emergent emotion, behavior and influence in a crowd, taking into account particularly the personality of members of the crowd. For this purpose, we have combined the OCEAN (Openness, Consciousness, Extraversion, Agreeableness, and Neuroticism) personality model with the OCC (Ortony, Clore, and Collins) emotional model to indicate the susceptibility of each of the five personality factors to feeling every emotion. Then we proposed an approach that uses first fuzzy logic for the emotional modeling of critical emotions of members of the crowd at the announcement or the presence of unusual events, in order to quantify emotions. Then, we model the behavior and the tendency towards actions using probability theory. Finally, the influence among the members of the crowd is modeled using the neighborhood principle and cellular automata.