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Modeling the Influence of Narratives on Collective Behavior Case Study: Using social media to predict the outbreak of violence in the 2011 London Riots

机译:建模叙事对集体行为的影响案例研究:使用社交媒体预测2011年伦敦暴动中暴力的爆发

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This paper considers the problem of understanding the influences of narratives or stories on individual and group behavior. Narrative theory describes how stories help people make sense of the world, and is being used to explain behavior in domains such as security, health care, and consumer behavior. We are interested in using narrative theory to develop better predictions of behavior and have developed a multi-methodology approach to combine narrative influence with system dynamics modeling of group behavior. Our model quantifies how individuals use narratives to understand current events and make decisions. We model the time-varying strength of cultural narratives as a degree of belief in the narrative's explanatory power, updated heuristically in response to observations about similarity between cultural narratives and current events. We use Twitter posts to measure narrative-significant observations in the real world. Using this approach, we investigate a case study of the violent riots in London in 2011 and demonstrate how relevant narratives can be identified, monitored, and included in behavior models to predict violent activity.
机译:本文考虑了理解叙事或故事对个人和团体行为的影响的问题。叙事理论描述了故事如何帮助人们理解世界,并被用来解释安全,医疗保健和消费者行为等领域的行为。我们有兴趣使用叙事理论来更好地预测行为,并且已经开发出一种多方法论的方法来将叙事影响与群体行为的系统动力学建模相结合。我们的模型量化了个人如何使用叙述来理解时事和做出决定。我们将文化叙事的时变力量建模为对叙事解释力的某种程度的信任,并根据对文化叙事与时事之间相似性的观察,以启发式的方式对其进行更新。我们使用Twitter帖子来衡量现实世界中具有叙述意义的观察结果。使用这种方法,我们调查了2011年伦敦暴力骚乱的案例研究,并演示了如何识别,监控相关叙事并将其包含在行为模型中以预测暴力活动。

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