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1/18/2023 0 Comments Our new paper using social media data to detect public response to hurricanes and climate change was published in Climate Risk ManagementOur new paper titled "Toward reduction of detrimental effects of hurricanes using a social media data analytic approach: How climate change is perceived?" has been published in Climate Risk Management. Below please find the abstract: "During natural disasters, there is a noticeably increased use of social media sites such as Twitter. Substantial research on social media data use during disasters has been conducted in the past decade since various social media platforms have emerged and gained popularity. This research highlights a thorough examination of the textual content of users’ posts shared on Twitter across the 48 contiguous U.S. states (CONUS) during hurricanes Harvey (2017) and Dorian (2019). We processed and analyzed 35 million tweets by classifying them into the main topics of concern discussed on Twitter over the CONUS. Sentiment analysis, topic modeling, and topic classification are a few of the Artificial Intelligence techniques from Natural Language Processing (NLP) that we employed in this work to analyze the Twitter data. Applying the NLP techniques on this large volume of data, made it possible to classify the tweet content into distinct categories in order to reveal valuable information on social response to hurricanes and assist crisis management agencies and disaster responders during and post disasters. Furthermore, this study offers helpful insights on the way climate change is discussed on Twitter before, during and after hurricane Harvey and Dorian. The outcome of this study uncovers detailed information on social response to hurricanes which benefits disaster managers and responders in reducing the detrimental effects of such extreme events and enhancing community readiness when these events occur."  Figure 2. Distribution of topics of concern along with tweets per one thousand population for (a) Hurricane Harvey (2017), and (b) Hurricane Dorian (2019) (source: Karimiziarani et al. in press)  Figure 6. Climate change Tweets per million people and sentiments for (a) Harvey (2017), and (b) Dorian (2019) (source: Karimiziarani et al. in press)
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8/2/2022 0 Comments Open PhD Position – coastal community resilience, risk perceptions, community engagement, Nature Based Solution The Environmental Decision Making Lab at the Department of Geography of the University of Alabama seeks a geography PhD student to focus on coastal community resilience, risk perceptions, community engagement under the theme of Nature Based Solution (NBS). The broader research team is focused on developing actionable design guidance for NBS (i.e., wetland restoration) along the US Gulf Coast. Our highly interdisciplinary group includes social scientists, wetland ecologists, water resource engineers, and government agency partners. Our goal is to develop guidance for wetland restoration activities optimized to reduce flooding and increase coastal community resilience. To accomplish this goal, we will employ a combination of community engagement, wetland plant community characterization, and state-of-the-art hydrologic and hydraulic modeling.
The successful candidate will be expected to start in spring, 2023. The candidate will work closely with social scientists, wetland ecologists, and water resource engineers, and our government partners to develop, assess, and communicate NBS design alternatives by engaging stakeholders in a knowledge co-production fashion. The candidate will be expected to work with the team to develop a plan for stakeholder engagement meetings, organize and facilitate stakeholder engagement activities, collect the data from the meetings, analyze the data, and report findings in peer-reviewed manuscripts. Through this work, the candidate will also be expected to develop hypothesis driven research based on their interests. The ideal candidate will have MS degrees in a relevant field (i.e., geography, urban and regional planning, environmental sociology, ecology, environmental science, or closely related field). The candidate should be excited about working on an interdisciplinary team; interacting with community partners, and conducting both basic and applied research. Further, experience with statistical analysis and programs (e.g., R, Stata, SPSS) and geographic information systems (e.g., ArcGIS, QGIS) are required. Experience with textual analysis programs (e.g., NVivo) is preferred but not required. Additionally, experience with scripting languages (e.g., R, Python, or Matlab) are preferred but not required. For more information, please contact Dr. Wanyun Shao (wshao1@ua.edu) 3/31/2022 0 Comments Our new paper has been published in the International Journal of Disaster Risk Reduction Our paper has been published in the International Journal of Disaster Risk Reduction (Impact factor: 4.32). Below please find the abstract: "Climate change has posed serious risks to coastal cities around the world. Effective urban disaster management calls for the coordination between the local government and residents. We propose a comprehensive framework to study urban disaster resilience under climate change with New Orleans of Louisiana in the U.S. as the study area. Municipal hazard mitigation must be sufficient to mitigate these hazards. Residents’ risk perceptions are a vital component of social vulnerability and can shape public decisions to increase disaster resiliency. Because climate change is expected to intensify, it becomes important to ensure that residents’ risk perceptions are considered when developing municipal plans to maximize regional resiliency. This research aims to identify a gap in the hazard mitigation process that can be closed to better prepare the community to manage coastal hazards. To achieve this, an online survey is distributed in the New Orleans metropolitan area to determine residents’ risk perceptions and expectations of the local government’s action. Policy analysis is conducted to identify the priorities held by municipal planners in these issues. Although there is no gap in the perception of risk and municipal mitigation of current coastal hazards, there is a gap between the municipal approach to climate change mitigation and the concern and expectation of actions the residents hold regarding the future effects of climate change. The approach to climate change should be reconsidered on a municipal level and new small-scale personal incentives should be promoted to maximize resiliency toward coastal hazards in the future."  Fig. 2 Framework of Convergent Research on Urban Disaster Resilience Our paper on community vulnerability to floods and hurricanes in the Gulf Coast has been recognized as the most cited paper in the journal Disasters.  Our new paper, entitled "Public awareness and perceptions of drought: A case study of two cities of Alabama" is published in Risk, Hazards, & Crisis in Public Policy. Below please find the abstract:
"Drought poses serious risks to society. There is, however, a lack of timely public awareness and sufficient public risk perceptions of this hazard due to its gradual onset. Timely and adequate public response is conducive to effective mitigation. It is imperative to understand how the public responds to drought. Using data from multiple sources, situated in two cities (Mobile and Huntsville) of Alabama, our study represents a comprehensive effort to understand public awareness and perceptions of drought. We have made several important findings. First, both physical and social contexts can influence public awareness of drought. Mobile is prone to a variety of coastal hazards and displays high social vulnerability. Residents in this city are thus more sensitive to environmental shocks, especially less frequent ones such as drought. Second, public awareness of drought is not constrained within the immediate drought impact area. Governmental declaration or regulation can bring the issue of drought from one area to the attention of the other area within one state. Third, public perceptions of drought numbers are negatively correlated with perceptions of precipitation but positively associated with perceptions of extreme heat. This finding reflects that the public perception of drought is in line with scientific understanding of drought. Drought is by definition persistent deficit of precipitation. Flash droughts can be triggered by heat waves which are more likely to occur during a drought. We end this study with recommendations for future studies." Our paper on pro-environmental behaviors in Copenhagen, Denmark has been published in Cities (Impact factor: 5.834). Below please find the abstract:
"What makes one green in a green capital? Previous research on actions to combat climate change using large national samples identifies how socio-demographic attributes and attitudes and belief profiles condition an individual’s propensity to take actions to improve the environment. Our approach investigates a smaller and more specific context – Copenhagen, Denmark – as a way to unlock particular pathways that animate individuals to combat climate change in a city considered to be one of the world’s greenest. Using a survey of approximately 1,000 Copenhageners, we compare socio-demographic characteristics with attitudinal and belief profiles to see how each explanation predicts four pro-environmental behaviors. We find that attitudes and beliefs, especially with environmental concern and political ideology, tend to be more associated with pro-environmental behaviors compared to socio-demographic characteristics. We conclude by discussing how even in the context of a green capital, familiar pathways to pro-environmental actions are found." Our new paper is published online in Sustainable Cities and Society (impact factor: 7.587). Below please find the abstract: "The use of social media platforms such as Twitter significantly increases during natural hazards. With the emergence of several social media platforms over the past decade, many studies have investigated the applications of these platforms during calamities. This study presents a comprehensive spatiotemporal analysis of textual content from millions of tweets shared on Twitter during Hurricane Harvey (2017) across several affected counties in southeast Texas. We propose a new Hazard Risk Awareness (HRA) Index, which considers multiple factors, including the number of tweets, population, internet use rate, and natural hazard characteristics per geographic location. We then map the HRA Index across southeast Texas. Utilizing a dataset of 18 million tweets, we employ Natural Language Processing (NLP) along with a set of statistical techniques to perform analysis on the textual data generated by Twitter users during Hurricane Harvey. This enables us to subdivide the tweet contents into several categories per county that would inform crisis management during the event. In all, our study provides valuable information at the county level before, during, and after Harvey that could significantly help disaster managers and responders to minimize the consequences of the event and improve the preparedness of the residents for it. Since HRA is derived based on the meteorological observations and some demographic information, depending on the availability of such dataset and the nature of the hazard (i.e., flood, wildfire, hurricane, and earthquake), this index can be calculated and employed for assessing the risk awareness of a community exposed to either of these natural hazards."  Figure 4. Hazard Risk Awareness index across the counties in southeast Texas affected by hurricane Harvey (Source: Karimiziarani et al. 2022)  Figure 6. Categorized tweets into humanitarian classes across the counties affected by Hurricane Harvey (Source: Karimiziarani et al. 2022) Our new paper has been published in Energy Research & Social Science (Impact factor: 6.834). Below please find the abstract:
"Climate change poses unprecedented risks to human society. Ample scientific evidence suggests that greenhouse gas emissions are the primary contributor to climate change. Large-scale greenhouse gas emissions are mainly caused by the consumption of fossil fuels. Thus, promoting renewable energy is one key strategy to mitigate these emissions and combat climate change. In this study, we investigate some potential driving forces of renewable energy deployment. We analyze panel data for 118 countries worldwide from 1995 to 2015. Results show that countries that are more vulnerable to climate change and have less carbon-intensive economies consume higher shares of renewable energy in their total energy consumption. We have explained the effects of the carbon tax even though its influence is statistically insignificant. Thus, this study complements the literature by identifying the impact of these three factors on renewable energy deployment. The findings also imply that countries would become more supportive of renewable energy when their economy is less intertwined with fossil fuels and there are relevant policies that offer incentives on renewables." 10/13/2020 1 Comment My analysis article on the Conversation I just published one analysis article on the Conversation. Below please find the last section:
"Hope for shrinking the power of misinformation The success of slowing the spread of COVID-19 hinges largely on people taking precautions, particularly wearing face masks and social distancing, until a safe and effective vaccine is widely available. One study on attitudes toward climate change offers some hope. It found that a large number of Republicans and conservatives actually hold more unstable views about climate change over time. This instability may mean they could be more open to listening to the evidence and changing their minds. If this is also the case with COVID-19, strategic science communications and community engagement activities may be able to make a difference and stop the rising death toll." Our new paper on perceptions of sea level rise has been published in Climatic Change (Impact factor: 4.743). Below please find the abstract: "Sea level rise (SLR) in the 21st century poses fundamental risks to coastal residents. The U.S. Gulf of Mexico Coast (Gulf Coast) is among the regions experiencing the most rapid relative SLR. Beyond its increasing exposure to SLR and related coastal flooding, the Gulf Coast is home to a large population and displays high social vulnerability. How the coastal population in this vulnerable region perceives the impending risks posed by SLR warrants further examination. Do coastal residents’ perceptions of SLR conform to the scientific projections? We adopt an integrative approach based on a 2019 survey merged with contextual data including percentage of population living within the Special Flood Hazard Area (SFHA) and social vulnerability at the county level, both of which are extracted from the Centers for Disease Control and Prevention. We find that public risk perceptions of sea level change are influenced by political predisposition, with Republicans being less likely than Democrats to expect SLR in the future. Moreover, SLR remains temporally distant issue among coastal residents. We then directly compare public expectations and scientific estimations of SLR in five states of the U.S. Gulf Coast region and find that coastal residents in states that have experienced faster SLR in the past are more optimistic about future SLR by underestimating its magnitude compared to those experiencing slower SLR. Moreover, we find that people likely conflate the severity with likelihood of SLR risk. The contextual force represented by percentage of population living within the SFHA designated by the Federal Emergency Management Agency (FEMA) can significantly influence individuals’ estimations of future SLR, with higher percentages leading to higher estimates. We suspect that the SFHA has become a powerful risk communication tool that influences coastal residents’ judgments about future risk.  Figure 3. Comparison of public estimation with scientific estimation of SLR at five locations in Texas, Louisiana, Mississippi and Alabama, Florida Panhandle, and Florida Peninsula along the U.S. Gulf Coast. Percentages assigned at lower level and upper level in each figures represent percentages of respondents who estimated future SLR to be lower than the 5th and higher than the 95th scientific estimates, respectively (Source: Shao et al. in press). |
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