Yu, X., Chen, J., & Liu, J. (2023). Examining the influence of social media on individual’s protective action taking during Covid-19 in China. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 295–308). Omaha, USA: University of Nebraska at Omaha.
Abstract: In the context of COVID-19, this study utilizes the Social Mediated Crisis Communication Model (SMCC) and the Protective Action Decision Model (PADM) to investigate the relationship between social media users' protective actions and crisis information during public health crises in China. By constructing a structural equation model, this study aims to identify the influencing factors that affect social media users' personal’s cognitive, emotional, and behavioral reactions given crisis relevant information. Results findings are that warning information can significantly increase risk perception; emotional responses are not significantly affected by warning information and risk perception; risk perception has a negative impact on information gathering and sharing behavior; risk perception has a significant mediating effect on the relationship between information features and protective action.
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Wang, D. (2023). Public Cognition and Perception on Social Media in Crisis. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 1081–1082). Omaha, USA: University of Nebraska at Omaha.
Abstract: Microblogging platforms have been increasingly used in crisis, facilitating more participatory communication between official response channels and affected communities. Despite the potential benefits, research has shown that disaster response organizations could not effectively utilize social media data due to data deluge (Knox 2022). To better understand the information needed for disaster response, we turn to the National Incident Management System Guidance for public information officers (PIOs) (NIMS Basic Guidance for PIOs 2020), the primary spokesperson for emergency management organizations. The guidance indicates that PIOs use social media for two major purposes, supporting their operational needs and gauging public perception of risk and incident response. To support the operational needs, the crisis informatics literature has heavily focused on information types supporting situational awareness, including serviceable, eyewitness or actionable information. However, the information representing public perception, such as people’s cognitive and perceptual processes in response to incidents, has been less addressed at scale. To bridge the gap between quantitative study in crisis informatics and information representing cognitive and perceptual processes and better support the task of PIOs, I focus on the study of people’s cognitive and perceptual processes on social media for my research. Cognitive and perceptual processes refer to the way that people pay attention to or process environmental inputs, including the mental activities of acquisition, processing or evaluation of environmental cues, social cues, and warnings. These processes reveal people’s perception of- and decision-making in response to potential threats. With this focus, I seek to answer the following research question: How could people’s cognitive and perceptual processes be inferred from their social media activities in crisis to benefit stakeholders in incident response? My interest in tracing this overall theme through a varied range of sub-tasks produces three more specific research questions: RQ1. How can information exposure and attention be operationalized to highlight cognitive and perceptual processes? RQ2. How do people’s perception of risk communications from stakeholders vary in crisis? RQ3. How could a principled and scalable pipeline be designed to identify people’s cognitive and affective perceptions on Twitter? I took cues from the Protective Action Decision Model (Lindell and Perry 2012) and leveraged baselines in the literature to address these research questions. To address the first research question, I proposed a metric that conceptualized and operationalized the predecision process. The proposed metric was incorporated into a pipeline and applied to two real-word events to recommend messages that represent the shift of collective attention of those locally affected with a specialized focus on cognitive and perceptual processes. To address the second research question, I went beyond the perception of risks to include perceptions of risk communications by stakeholders. I performed an empirical study of the relation between risk communications by stakeholders and different kinds of public perceptions (Lindell and Perry 2012). To address the third research question, I proposed a future work to provide benchmark coding schemes, datasets and models to quantitatively identify information representing cognitive and perceptual processes. I will leverage existing benchmark datasets in the literature (Olteanu et al. 2014; Imran et al. 2016; Alam et al. 2018; Zahra et al. 2020; Rudra et al. 2017; Mazloom et al. 2018; Purohit et al. 2018) and coding schemes in qualitative studies (Trumbo et al. 2016; Demuth et al. 2018) and create benchmark classification models.
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Thomas J. Huggins, Wenbo Zhang, & Eva Yang. (2023). Evaluating Flood-Related Decision-Making and the Role of Information Technologies. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 45–55). Palmerston North, New Zealand: Massey Unversity.
Abstract: The proposed research consists of an innovative research design and piloting to compare traditional and contemporary approaches to loss-related decisions, concerning flooding risk in particular. By developing and implementing the integration of multiple methods, the proposed research aims to provide detailed and compelling evidence of how disaster-related decisions can be evaluated using an out-of-frame (capacity) and out-of-sample (occurrence) criterion, i.e. instead of taking a more reductive approach to real world problems. Together with other research being conducted around the world, the current initiative will address the contemporary scientific problem of whether traditionally axiomatic or ecological rationality should be used for evaluating disaster-related decisions. Where ecological rationality is found to be more effective, the same research will inform how ecologically rational approaches to flood risk can be improved through promoting particular areas of an information display or interface under particular conditions.
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Hannes Restel, Eridy Lukau, Sebastian Sterl, & Lars Gerhold. (2022). Detecting Covid-19 Relevant Situations using Privacy-by-Design based Mobile Experience Sampling. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 506–527). Tarbes, France.
Abstract: To observe psychosocial effects of the Covid-19 pandemic on the population, multiple retrospective studies have been performed in Germany. However, this approach may lead to response bias regarding affective and cognitive processes as it fails to capture situations as they occur (‘in situ’). Identifying those situations in daily life where individuals are emotionally and cognitively affected by Covid-19 can provide valuable insights for mobile experience sampling method studies (MESM) that evaluate participants’ affective and cognitive processes. This study presents an MESM solution (a self-developed smartphone app and server backend) to detect Covid-19 induced ‘in-situ frames’ which was successfully used in a long-term psychosocial study in Berlin (Germany) from November 2021 to January 2022. As highly sensitive personal data (e.g., emotional state, vaccination status and infection state, socio-demographics) have been collected, the solution places a strong emphasis on privacy, pseudo-anonymization, data-minimization, and security. To support long-time motivation for the participants, good usability and user experience containing gamification elements were also realized. The results indicate that Covid-19-related situations expressed by means of a high emotional risk perception could be identified even though participants located themselves in “rather Covid-19 free” private spaces.
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Jennings Anderson, Marina Kogan, Melissa Bica, Leysia Palen, Kenneth Anderson, Rebecca Morss, et al. (2016). Far Far Away in Far Rockaway: Responses to Risks and Impacts during Hurricane Sandy through First-Person Social Media Narratives. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: When Hurricane Sandy swept over the US eastern seaboard in October 2012, it was the most tweeted about event at the time. However, some of the most affected areas were underrepresented in the social media conversation about Sandy. Here, we examine the hurricane-related experiences and behaviors shared on Twitter by residents of Far Rockaway, a New York City neighborhood that is geographically and socioeconomically vulnerable to disasters, which was significantly affected by the storm. By carefully filtering the vast Twitter data, we focus on 41 Far Rockaway residents who offer rich personal accounts of their experience with Sandy. Analyzing their first-person narratives, we see risk perception and protective decision-making behavior in their data. We also find themes of invisibility and neglect when residents expressed feeling abandoned by the media, the city government, and the overall relief efforts in the aftermath of Sandy.
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