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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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8/31/2022 2 Comments Our new paper on the socio-geographic patterns of rescue requests during Hurricane Harvey has been published in Findings Our paper on the socio-geographic patterns of rescue requests during Hurricane Harvey has been published in Findings. Below is the abstract: "We analyze a public dataset of rescue requests for the Houston Metropolitan Area during Hurricane Harvey (2017) from the Red Cross. This dataset contains information including the location, gender, and emergency description in each requester’s report. We reveal the spatial distribution of the rescue requests and its relationship with indicators of the social, physical, and built environment. We show that the rescue request rates are significantly higher in regions with higher percentages of children, male population, population in poverty, or people with limited English, in addition to regions with higher inundation rate or worse traffic condition during Hurricane Harvey. The rescue request rate is found to be statistically uncorrelated with the percentage of flood hazard zone designated by the Federal Emergency Management Agency (FEMA)."  Figure 1.Spatial Distribution of Event-related Variables in Each Zip Code. a). Percentage of people who sought rescues during Harvey, b). Traffic index during Harvey, c). Inundation index during Harvey. 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 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 new paper, entitled "Understanding the Influence of Political Orientation, Social Network, and Economic Recovery on COVID-19 Vaccine Uptake among Americans" has been published online in Vaccine (Impact factor: 3.641). Below please find the abstract:
"The COVID-19 pandemic poses unprecedented risks to the well-being of Americans. To control the pandemic, a sufficient proportion of the population needs to be vaccinated promptly. Despite the proven efficacy and widespread availability, vaccine distribution and administration rates remain low. Thus, it is important to understand the public behavior of COVID-19 vaccination. This study aims to identify determinants at multiple levels that promote or inhibit one’s vaccine uptake. We combine individual-level data from a national survey conducted in the summer of 2021 with corresponding state-level indicators. Findings of multilevel logistic regression show that political orientation, social network, and economic recovery altogether have significant influence. We articulate that individual decisions to take the vaccine are a function of their personal characteristics and are also rooted in their home state’s political, public health, and economic contexts. These findings contribute to the literature and have policy implications. Knowledge of the profiles among people who take/refuse the vaccine provides essential information to leverage certain factors and maximize vaccine uptake to mitigate the pandemic’s devastating impact." 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, entitled "Perceptions of earthquake risks and knowledge about earthquake response among movement challenged persons in Dhaka City of Bangladesh, has been published in the International Journal of Disaster Risk Reduction (impact factor: 4.32). Below please find the abstract:
"Dhaka, Bangladesh is one Asian city that is at high risk of earthquakes. Persons with physical disabilities, particularly movement challenged persons (MCPs), is highly vulnerable to earthquakes because of their mobility impairment. This study aims to explore risk perceptions of earthquakes and knowledge about response to earthquakes among MCPs in Dhaka through a 2020 survey of 455 respondents. Four risk perception measures are developed: perceived probability of an earthquake, fear, perceived threat to life, and perceived damage to property in the event of an earthquake. Subsequent factor analysis reveals that these four measures are loaded on one factor named risk perception. Measures of knowledge about response to earthquakes include knowledge of where to seek shelter while being inside and outside of home during an earthquake, location of critical facilities and existence of evacuation route in the locality as well as their knowledge about National Plan for Disaster Management (NPDM) of Bangladesh. This study finds that mobility aid, age, income, education, building structure, previous experience with earthquake are significantly related to risk perceptions. MCPs who have participated in the training know what they should do in the event of an earthquake irrespective of being outside or inside of home. MCPs with more education are more likely to know about NPDM and the existence of fault lines in Bangladesh. Lack of accessibility in training centers and lack of dissemination of information about training are key reasons behind MCPs not participating in the training." Our analysis article reflecting on the COVID-19 year was just published on the Conversation:
"Even though Americans shared the experience of living through a global pandemic, their individual attitudes towards it differed and evolved – sometimes dramatically... Overall, our research shows the combination of timely information with trusting, well-connected communities, is most likely to result in collective risk mitigation behavior. Perhaps these insights can help the U.S. prepare better for the next pandemic." Our paper entitled "Understanding American public support for COVID-19 risk mitigation: The role of political orientation, socio-demographic characteristics, personal concern, and experience" has been published the International Journal of Public Health (Impact factor: 3.38). Below please find the abstract:
"Objectives: COVID-19 is the most challenging public health crisis in decades in the United States. It is imperative to enforce social distancing rules before any safe and effective vaccines are widely available. Policies without public support are destined to fail. This study aims to reveal factors that determine the American public support for six mitigation measures (e.g., cancel gatherings, close schools, restrict non-essential travel). Methods: Based on a nationally representative survey, this study uses Structural Equation Modelling to reveal the relationships between various factors and public support for COVID-19 mitigation. Results: 1). Democrats are more likely than Republicans to support mitigation measures; 2).Favorability towards the political leader (Biden or Trump) can slant public support for COVID-19 mitigation measures among different segments of the public; 3). Indirect experience, rather than direct experience with COVID-19 can motivate people to support mitigation; 4). Concern for COVID-19 is a strong motivator of support for mitigation. Conclusion: Political polarization poses an enormous challenge to societal well-being during a pandemic. Indirect experience renders COVID-19 an imminent threat." Our new paper entitled "Understanding the effects of individual and state-level factors on American public response to COVID-19" has been accepted for publication in American Journal of Health Promotion (Impact factor: 2.87). Below please find the abstract: "Purpose: To examine multilevel predictors on American public response to COVID–19. Design: Multilevel study. Setting: A national survey was conducted by Qualtrics from August 24 to September 11, 2020. The state-level variables were constructed on data from multiple sources. Subjects: 2,440 respondents 18 years and older from all 50 states and D.C. Measures: The outcome variable is the public response to COVID–19 measured by threat perception, behavioral adjustment, and policy support. The predictors include individual-level sociodemographic factors and state-level indicators about public health conditions, political context, and economic recovery. Analysis: Multilevel structural equation modeling is used for statistical estimation. Results: People from states with more COVID–19 cases (β=0.020, p<0.1), mandatory face mask policies (β=0.069, p<0.05), and liberal governments (β=0.002, p<0.05) are more likely to respond while people from states whose economies have recovered closer to the pre-pandemic level are less likely to do so (β=-0.005, p<0.05). Regarding individual-level predictors, older people (β=0.005, p<0.001) and people with better education (β=0.029, p<0.01), leaning toward the Democrat Party (β=0.066, p<0.001) and liberal political ideology (β=0.094, p<0.001), and have stronger generalized trust (β=0.033, p<0.001) are more likely to respond than their counterparts. Conclusion: Differences in the public response to the pandemic stem from variations in individual characteristics and contextual factors of states where people live. These findings contribute to the rapidly growing literature and have implications for public health policies."  Figure 1. Multilevel Structural Equation Modeling Diagram (Hao and Shao 2021b)  Figure 2. The Influence of State-Level Factors on Public Response to COVID–19 (Hao and Shao 2021b) |
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