PDF(Pubmed)
Abstract：
The rise in global temperatures due to climate change has escalated the frequency and intensity of wildfires worldwide. Beyond their direct impact on physical health, these wildfires can significantly impact mental health. Conventional mental health studies predominantly rely on surveys, often constrained by limited sample sizes, high costs, and time constraints. As a result, there is an increasing interest in accessing social media data to study the effects of wildfires on mental health.
In this study, we focused on Twitter users affected by the California Tubbs Fire in 2017 to extract data signals related to emotional well-being and mental health. Our analysis aimed to investigate tweets posted during the Tubbs Fire disaster to gain deeper insights into their impact on individuals. Data were collected from October 8 to October 31, 2017, encompassing the peak activity period. Various analytical methods were employed to explore word usage, sentiment, temporal patterns of word occurrence, and emerging topics associated with the unfolding crisis.
The findings show increased user engagement on wildfire-related Tweets, particularly during nighttime and early morning, especially at the onset of wildfire incidents. Subsequent exploration of emotional categories using Linguistic Inquiry and Word Count (LIWC) revealed a substantial presence of negative emotions at 43.0%, juxtaposed with simultaneous positivity in 23.1% of tweets. This dual emotional expression suggests a nuanced and complex landscape, unveiling concerns and community support within conversations. Stress concerns were notably expressed in 36.3% of the tweets. The main discussion topics were air quality, emotional exhaustion, and criticism of the president\'s response to the wildfire emergency.
Social media data, particularly the data collected from Twitter during wildfires, provides an opportunity to evaluate the psychological impact on affected communities immediately. This data can be used by public health authorities to launch targeted media campaigns in areas and hours where users are more active. Such campaigns can raise awareness about mental health during disasters and connect individuals with relevant resources. The effectiveness of these campaigns can be enhanced by tailoring outreach efforts based on prevalent issues highlighted by users. This ensures that individuals receive prompt support and mitigates the psychological impacts of wildfire disasters.
In this study, we focused on Twitter users affected by the California Tubbs Fire in 2017 to extract data signals related to emotional well-being and mental health. Our analysis aimed to investigate tweets posted during the Tubbs Fire disaster to gain deeper insights into their impact on individuals. Data were collected from October 8 to October 31, 2017, encompassing the peak activity period. Various analytical methods were employed to explore word usage, sentiment, temporal patterns of word occurrence, and emerging topics associated with the unfolding crisis.
The findings show increased user engagement on wildfire-related Tweets, particularly during nighttime and early morning, especially at the onset of wildfire incidents. Subsequent exploration of emotional categories using Linguistic Inquiry and Word Count (LIWC) revealed a substantial presence of negative emotions at 43.0%, juxtaposed with simultaneous positivity in 23.1% of tweets. This dual emotional expression suggests a nuanced and complex landscape, unveiling concerns and community support within conversations. Stress concerns were notably expressed in 36.3% of the tweets. The main discussion topics were air quality, emotional exhaustion, and criticism of the president\'s response to the wildfire emergency.
Social media data, particularly the data collected from Twitter during wildfires, provides an opportunity to evaluate the psychological impact on affected communities immediately. This data can be used by public health authorities to launch targeted media campaigns in areas and hours where users are more active. Such campaigns can raise awareness about mental health during disasters and connect individuals with relevant resources. The effectiveness of these campaigns can be enhanced by tailoring outreach efforts based on prevalent issues highlighted by users. This ensures that individuals receive prompt support and mitigates the psychological impacts of wildfire disasters.
摘要：
■由于气候变化导致的全球气温上升加剧了全球野火的频率和强度。除了它们对身体健康的直接影响，这些野火会显著影响心理健康。传统的心理健康研究主要依靠调查，通常受到有限的样本量的限制，高成本,和时间限制。因此,人们越来越有兴趣访问社交媒体数据来研究野火对心理健康的影响。
■在这项研究中，我们专注于2017年受加州塔布斯火灾影响的Twitter用户，以提取与情绪健康和心理健康相关的数据信号。我们的分析旨在调查在Tubbs火灾期间发布的推文，以更深入地了解其对个人的影响。数据收集时间为2017年10月8日至10月31日，涵盖活动高峰期。采用了各种分析方法来探索单词的用法，情绪,单词出现的时间模式，以及与不断发展的危机相关的新兴话题。
■调查结果显示，用户对与野火相关的推文的参与度增加，特别是在夜间和清晨，尤其是在野火事件开始的时候.随后使用语言查询和单词计数（LIWC）对情绪类别进行的探索显示，负面情绪的存在占43.0％，在23.1%的推文中与同时的正面并列。这种双重情感表达暗示了一种微妙而复杂的景观，在对话中揭示关注和社区支持。压力担忧在36.3％的推文中尤为明显。主要讨论的议题是空气质量,情绪疲惫,以及对总统对野火紧急情况的反应的批评。
■社交媒体数据，特别是在野火期间从Twitter收集的数据，提供了一个机会，立即评估对受影响社区的心理影响。公共卫生当局可以使用这些数据在用户更活跃的地区和时间发起有针对性的媒体宣传活动。此类运动可以提高人们对灾难期间心理健康的认识，并将个人与相关资源联系起来。可以通过根据用户强调的普遍问题调整外联工作来提高这些活动的有效性。这确保个人得到及时的支持，并减轻野火灾害的心理影响。
■在这项研究中，我们专注于2017年受加州塔布斯火灾影响的Twitter用户，以提取与情绪健康和心理健康相关的数据信号。我们的分析旨在调查在Tubbs火灾期间发布的推文，以更深入地了解其对个人的影响。数据收集时间为2017年10月8日至10月31日，涵盖活动高峰期。采用了各种分析方法来探索单词的用法，情绪,单词出现的时间模式，以及与不断发展的危机相关的新兴话题。
■调查结果显示，用户对与野火相关的推文的参与度增加，特别是在夜间和清晨，尤其是在野火事件开始的时候.随后使用语言查询和单词计数（LIWC）对情绪类别进行的探索显示，负面情绪的存在占43.0％，在23.1%的推文中与同时的正面并列。这种双重情感表达暗示了一种微妙而复杂的景观，在对话中揭示关注和社区支持。压力担忧在36.3％的推文中尤为明显。主要讨论的议题是空气质量,情绪疲惫,以及对总统对野火紧急情况的反应的批评。
■社交媒体数据，特别是在野火期间从Twitter收集的数据，提供了一个机会，立即评估对受影响社区的心理影响。公共卫生当局可以使用这些数据在用户更活跃的地区和时间发起有针对性的媒体宣传活动。此类运动可以提高人们对灾难期间心理健康的认识，并将个人与相关资源联系起来。可以通过根据用户强调的普遍问题调整外联工作来提高这些活动的有效性。这确保个人得到及时的支持，并减轻野火灾害的心理影响。
