Social media generates a significant amount of information in terms of perceptions, emotions, and sentiments. We present an economic analysis using the information provided by Twitter messages, describing impressions and reactions to wildfires occurring in Spain and Portugal. We use natural language processing techniques to analyze this text information. We generate a hedonometer estimate on how sentiments about wildfires vary with exposure, measured via Euclidean distance from the catastrophic event, and air quality. We find that direct exposure to wildfires significantly decreases the expressed sentiment score and increases the expressions of fear and political discontent (protest). Economic valuation of these losses has been computed to be between 1.49€–3.50€/year/Kilometer of distance to the closest active fire. Welfare losses in terms of air quality have been computed as 4.43€–6.59€/day of exposure.

社交媒体会在感知、情感和情绪方面产生大量信息。我们使用 Twitter 消息提供的信息进行经济分析，描述对西班牙和葡萄牙发生的野火的印象和反应。我们使用自然语言处理技术来分析这些文本信息。我们通过与灾难性事件的欧几里德距离和空气质量来测量野火的情绪如何随暴露量而变化，我们生成了一个快乐计估计。我们发现，直接暴露于野火会显着降低表达的情绪得分，并增加恐惧和政治不满（抗议）的表达。这些损失的经济估值已计算为 1.49 欧元至 3.50 欧元/年/公里到最近的活动火灾的距离。