Social media data and housing recovery following extreme natural hazards

Jamali, Mehdi; Nejat, Ali; Moradi, Saeed; Ghosh, Souparno; Cao, Guofeng

doi:10.1016/j.ijdrr.2020.101788

Cited by 25 publications

(7 citation statements)

References 66 publications

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“…Although labeling the factors should be descriptive and consistent with other taxonomies in the field (Pett et al 2003), it is, in general, subjective and inductive (Williams et al 2010). For example, job can be labeled as basic needs (Karpman et al 2018) because it enables individuals to fulfill their basic needs, categorized as community-related needs because infrastructure investment programs can affect the creation and distribution of jobs (Haughwout 1999;Heintz et al 2009), or marked as financial needs due to its association with income, which is a natural fit for financial classification (Jamali et al 2020). Once loadings are calculated, factor scores for each item are estimated.…”

Section: Analysis Results and Discussionmentioning

confidence: 99%

Prioritizing Post Disaster Recovery Needs: Academicians versus Practitioners

Nejat¹,

Moradi²

2021

Preprint

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Effective knowledge transfer between researchers and practitioners within the hazards and disaster domain has long been a challenging task. The diversity of hazard researchers and practitioners, as well as the high stakes of applying research outcomes, have contributed to the issue. This research aims to explore potential discrepancies between researchers and practitioners’ perspectives regarding post-disaster recovery needs. To achieve the objective of this research, a survey was developed and conducted during the 2019 Natural Hazards Workshop in Broomfield, Colorado, which is host to individuals from various career backgrounds, including researchers, practitioners, policymakers, students, etc. Exploratory factor analysis and elastic net regression were used to provide a link between individuals’ awareness of these challenges and their personal attributes. Results highlighted the discrepancies between researchers and practitioners in how they perceive and prioritize recovery needs. Results from this research can be used to bridge the existing perception gap with the goal of devising policies that can improve recovery by addressing the needs more realistically.

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Section: Analysis Results and Discussionmentioning

confidence: 99%

Prioritizing Post Disaster Recovery Needs: Academicians versus Practitioners

Nejat¹,

Moradi²

2021

Preprint

Self Cite

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“…This suggests that social media use, and in particular Twitter messages, are reliable indicators of public awareness (Bird et al 2012;Kryvasheyeu et al 2016;Wang et al 2016;Silver and Andrey 2019). Globally, researchers have taken advantage of the increasing volume of social data provided by the public to improve understanding of how people respond to (Wang et al 2016;Reynard and Shirgaokar 2019;Martín et al 2020) and recover from (Jamali et al 2020) sudden-onset disasters such as floods, bushfires, earthquakes and cyclones/hurricanes. Social media has also been used for early detection and tracking of such events (Wang et al 2016) and to assess the level of damage afterwards (Kryvasheyeu et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Responses to heat waves: what can Twitter data tell us?

et al. 2023

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Increasing average temperatures and heat waves are having devasting impacts on human health and well-being but studies of heat impacts and how people adapt are rare and often confined to specific locations. In this study, we explore how analysis of conversations on social media can be used to understand how people feel about heat waves and how they respond. We collected global Twitter data over four months (from January to April 2022) using predefined hashtags about heat waves. Topic modelling identified five topics. The largest (one-third of all tweets) was related to sports events. The remaining two-thirds could be allocated to four topics connected to communication about climate-related heat or heat waves. Two of these were on the impacts of heat and heat waves (health impacts 20%; social impacts 16%), one was on extreme weather and climate change attribution (17%) and the last one was on perceptions and warning (13%). The number of tweets in each week corresponded well with major heat wave occurrences in Argentina, Australia, the USA and South Asia (India and Pakistan), indicating that people posting tweets were aware of the threat from heat and its impacts on the society. Among the words frequently used within the topic ‘Social impacts’ were ‘air-conditioning’ and ‘electricity’, suggesting links between coping strategies and financial pressure. Apart from analysing the content of tweets, new insights were also obtained from analysing how people engaged with Twitter tweets about heat or heat waves. We found that tweets posted early, and which were then shared by other influential Twitter users, were among the most popular. Finally, we found that the most popular tweets belonged to individual scientists or respected news outlets, with no evidence that misinformation about climate change-related heat is widespread.

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“…Increasingly, the public turns to social media during crises to share the latest information while agencies (governmental, nongovernmental or non-institutional) use social media for formal communication of updated information, warnings and speci c advice, or give directions to the public and stakeholders such as volunteers (Bird et al 2012; Abedin and Babar 2018). Many studies have shown that the number of social media messages from people close to events increases substantially immediately before and during their occurrence, suggesting that social media use, and in particular Twitter messages, are reliable indicators of public awareness (Bird et (Jamali et al 2020) sudden onset disasters such as oods, bush res, earthquakes and cyclones/hurricanes. Social media has also been used for early detection and tracking of such events (Wang et al 2016) and to assess the level of damage afterwards (Kryvasheyeu et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Responses to heat waves: what can Twitter data tell us?

Zander

Rieskamp

Mirbabaie

et al. 2022

Preprint

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Increasing average temperatures and heat waves have devasting impacts on human health and well-being but studies on heat impacts and how people adapt are rare and often confined to specific locations. In this study we aimed to explore how social media data can be used to generate knowledge about how people feel about heat waves through an analysis of their conversations. We collected global Twitter data over two months (January and February 2022) using predefined hashtags about heatwaves. Topic modelling revealed five clusters of which three were related to communications about climate change related heat, covering 76% of all tweets. These three clusters included one on the impacts of heat and heatwaves (34%), one on perceptions of weather and heat (28%) and one on extreme weather and climate change (14%). The remaining 24% of tweets were on sport events or films and music. The number of tweets in each week corresponded well with major heat wave occurrences in Argentina, Australia and India, indicating that people are aware of the threat from heat and its impacts on the society, although not much could be learned in terms of personal coping and preparedness strategies. Apart from the content of tweets, a great deal could be learned in terms of how people engaged with Twitter tweets about heat or heat waves. We found that tweets posted early, and which were shared by other influential Twitter users, were among the most popular. Finally, we found that the most popular tweets belonged to individual scientists or respected news outlets, with no evidence of wide-spread misinformation about climate change related heat.

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Social media data and housing recovery following extreme natural hazards

Cited by 25 publications

References 66 publications

Prioritizing Post Disaster Recovery Needs: Academicians versus Practitioners

Prioritizing Post Disaster Recovery Needs: Academicians versus Practitioners

Responses to heat waves: what can Twitter data tell us?

Responses to heat waves: what can Twitter data tell us?

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