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An approach for emotions and behavior modeling in a crowd in the presence of rare events

机译：在稀有事件存在下的人群情感和行为建模方法

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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.
机译：日常生活中的常见现象是，当发生或宣布发生一件奇怪的事件时，普通人群会完全改变，表现出不同的强烈情绪，有时甚至出现无法控制的暴力行为。这些扰乱人群组织的情绪和行为在我们的研究中受到关注，我们试图预测这些可疑的情况，并在正确的时间做出正确的决定提供帮助。此外，解决人群灾难的大多数模型都属于物理方法或认知方法。他们研究行人流动和避免碰撞等，并使用步行速度和视角。但是，在这项工作中，我们基于行为规则方法，旨在模拟人群中出现的情绪，行为和影响，尤其要考虑人群的个性。为此，我们将OCEAN（开放性，意识，外向性，和A性和神经质）人格模型与OCC（Ortony，Clore和Collins）情感模型相结合，以表明五个人格因素中的每一个都容易感觉到情感。然后，我们提出了一种方法，该方法使用第一模糊逻辑对人群成员在宣布或出现异常事件时的关键情感进行情感建模，以量化情感。然后，我们使用概率论对行为和行为倾向进行建模。最后，使用邻域原理和元胞自动机对人群成员之间的影响进行建模。

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