利用社交媒体数据的感知风险指数:评估微博火灾的严重程度

IF 4.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Carmen De Maio, Giuseppe Fenza, Mariacristina Gallo, Vincenzo Loia, Alberto Volpe
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引用次数: 0

摘要

火灾对环境、基础设施和人类安全构成重大威胁,通常会迅速蔓延,造成经济损失和生命危险等广泛后果。及早发现并迅速应对火灾爆发对减轻其影响至关重要。基于卫星的监测虽然有效,但可能会错过短暂的火灾或室内火灾。本文介绍了一种新颖的感知风险指数(PRI),该指数与卫星数据互为补充,利用社交媒体数据来深入了解火灾事件的严重性。根据统计分析结果,PRI 将与火灾有关的推文数量和相关的情绪表达纳入其中,以衡量感知风险。该指数的评估包括开发一个综合系统,用于收集、分类、注释社交媒体帖子并将其与卫星数据相关联,同时在一个交互式仪表板中展示评估结果。使用各种真实火灾推文数据集的实验结果表明,PRI 与卫星探测到的火灾亮度值之间的平均最佳相关性为 77%。这种相关性延伸到了相应火灾的实际强度,展示了社交媒体平台在为应急响应和决策提供信息方面的潜力。拟议的 PRI 被证明是持续监测工作的宝贵工具,有可能捕捉到卫星遗漏的火灾数据。这有助于制定更有效的战略,减轻火灾事件对环境、基础设施和安全的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Perceived Risk Index Leveraging Social Media Data: Assessing Severity of Fire on Microblogging

A Perceived Risk Index Leveraging Social Media Data: Assessing Severity of Fire on Microblogging

Fires represent a significant threat to the environment, infrastructure, and human safety, often spreading rapidly with wide-ranging consequences such as economic losses and life risks. Early detection and swift response to fire outbreaks are crucial to mitigating their impact. While satellite-based monitoring is effective, it may miss brief or indoor fires. This paper introduces a novel Perceived Risk Index (PRI) that, complementing satellite data, leverages social media data to provide insights into the severity of fire events. In the light of the results of statistical analysis, the PRI incorporates the number of fire-related tweets and the associated emotional expressions to gauge the perceived risk. The index’s evaluation involves the development of a comprehensive system that collects, classifies, annotates, and correlates social media posts with satellite data, presenting the findings in an interactive dashboard. Experimental results using diverse datasets of real-fire tweets demonstrate an average best correlation of 77% between PRI and the brightness values of fires detected by satellites. This correlation extends to the real intensity of the corresponding fires, showcasing the potential of social media platforms in furnishing information for emergency response and decision-making. The proposed PRI proves to be a valuable tool for ongoing monitoring efforts, having the potential to capture data on fires missed by satellites. This contributes to the development to more effective strategies for mitigating the environmental, infrastructural, and safety impacts of fire events.

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来源期刊
Cognitive Computation
Cognitive Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-NEUROSCIENCES
CiteScore
9.30
自引率
3.70%
发文量
116
审稿时长
>12 weeks
期刊介绍: Cognitive Computation is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of natural and artificial cognitive systems. It provides a new platform for the dissemination of research, current practices and future trends in the emerging discipline of cognitive computation that bridges the gap between life sciences, social sciences, engineering, physical and mathematical sciences, and humanities.
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