Content-based user classifier to uncover information exchange in disaster-motivated networks

Babvey, Pouria; Gongora-Svartzman, Gabriela; Lipizzi, Carlo; Ramírez-Márquez, José Emmanuel

doi:10.1371/journal.pone.0259342

Cited by 5 publications

(2 citation statements)

References 46 publications

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“…Twitter for Prediction of Physical and Mental Health Needs research survey in such circumstances is an ethical issue and also poses technical difficulties in administering the survey while ensuring the investigators' safety. Research using social network services (SNS) may help address this particular problem (Babvey et al 2021;Arthur et al 2018;Bennett 2018). Numerous studies have used tweet analysis to evaluate the Great East Japan Earthquake (Aoki et al 2018;Takayasu et al 2015;Jung and Moro 2014).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Real-Time Prediction of Medical Demand and Mental Health Status in Ukraine under Russian Invasion Using Tweet Analysis

Fujii

Kunii

Nonaka

et al. 2023

Tohoku J. Exp. Med.

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Russia's invasion of Ukraine (February 24, 2022) has begun and there are concerns about the impact on health care supply and mental health. This study analyzed tweets in the Ukrainian language to capture the medical needs and mental health conditions in wartime Ukraine by focusing on ostensibly relevant words. The number of tweets containing the keywords and their overall proportion was compared before and after the Russian invasion of Ukraine. The survey period was divided into four phasesthe pre-2022 Russian invasion, acute phase (4 weeks), subacute phase (12 weeks), and the chronic phase (8 weeks) up to August 10, 2022. The analysis targeted tweets sent in Ukrainian. The tweets were screened using a set of six classes with 75 key groups and 303 Ukrainian (204 original Japanese) keywords. Overall, 98,526,440 tweets were analyzed, with a pre-invasion and post-onset average of 1,096,976 and 3,328,243 tweets/week (a 3.0-fold increase), respectively. Of these, 3,197,443 tweets contained the keywords, with a pre-invasion and invasion average of 26,241 and 114,640 tweets/week (a 4.4-fold increase), respectively. The post-onset phase witnessed a considerable increase in all classes-medical services, treatment, medical resources, medical situations, and special situations-but not in the symptom class. Keywords related to psychological distress and anxiety immediately increased during the acute phase; those related to depression and post-traumatic stress reactions continued increasing as the invasion persisted, which may have reflected the mental state of those impacted. Analyzing tweets is useful for predicting people's real-time physical and mental health needs during wartime. Keywords: Social Network System; Twitter; physical and mental health needs; human-induced hazards; Ukraine operation." On the same day, military operations began throughout Ukraine, including in 3 the vicinity of the Ukrainian capital, Kiev (Russian Ministry of Foreign Affairs 2022). 4 The two countries have been engaged in a series of confrontations and conflicts, 5 beginning in the Donbass region of southeastern Ukraine, including the annexation of the 6 Crimean Peninsula in 2014; as of the end of October 2022, military operations are still 7 ongoing. This military conflict has predominantly been fought inside Ukraine. Ukrainian 8 citizens are exposed to daily threats to their lives, including shelling (Adams et al. 2022). 9 A human-induced hazard is similar to sudden-onset natural hazards; the 2022 Russian invasion clearly created a different environment-a disaster. Concerns exist regarding the impact on the medical supply and mental health, and the sustainability of daily life (Patel and Erickson 2022; Awuah et al. 2022).Life-threatening events-natural hazards, wars, accidents, crimes, and abusetrigger acute stress reactions that precipitate the development of post-traumatic stress disorder (PTSD). Numerous mental health surveys and research projects have examined past disasters caused by natural hazards and chemical, biological, radiologica...

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Section: Accepted Manuscriptmentioning

confidence: 99%

Real-Time Prediction of Medical Demand and Mental Health Status in Ukraine under Russian Invasion Using Tweet Analysis

Fujii

Kunii

Nonaka

et al. 2023

Tohoku J. Exp. Med.

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“…Two additional criteria were added to narrow the scope of the systematic review and to ensure that the studies included in this review were evidence-informed (i.e., relying on data) and focused on public alert and warning systems in the social science realm. These two criteria are: (5) studies had to be empirical (i.e., use quantitative or qualitative data) and (6) articles could not focus primarily on the technological applications of the public alert and warning system.…”

Section: Selection Criteriamentioning

confidence: 99%

Public Alert and Warning System Literature Review in the USA: Identifying Research Gaps and Lessons for Practice

Sadiq

Okhai

Tyler³

et al. 2022

Preprint

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As emergencies continue to impact communities in the United States on an unprecedented scale, it is imperative for communities to look for effective ways to keep people safe and reduce future impacts. Public alert and warning systems are an effective means of accomplishing these goals. As such, researchers have studied public alert and warning systems extensively in the United States. Due to the plethora of studies on public alert and warning systems, a systematic and comprehensive synthesize is needed to understand what has been studied and their major findings and identify practical lessons that can be used to further improve public alert and warning systems. Hence, the goal of this study is to answer the following two questions: (1) What are the major findings from public alert and warning system research? (2) What policy and practical lessons can be gleaned from public alert and warning system research to improve public alert and warning system research and practice? We answer these questions by conducting a systematic and comprehensive review of the public alert and warning system literature, starting with a keyword search. The search produced 1,737 studies, and we applied six criteria (e.g., the study has to be a peer-reviewed article, dissertation, or conference paper), which narrowed the number of studies to 100. After analyzing the 100 studies, the results reveal 12 emergent themes regarding the major findings from public alert and warning system research. The results also reveal eight emergent themes related to the policy and practical lessons. We then offer recommended topics for future research as well as outline some policy and practical recommendations. We conclude by summarizing the findings and discussing the limitations of the study.

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Impact of Media Information on Social Response in Disasters: A Case Study of the Freezing-Rain and Snowstorm Disasters in Southern China in 2008

He,

Duan,

Zhou

et al. 2024

Int J Disaster Risk Sci

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Disaster information content is an objective mapping of disaster situations, social response, and public opinions. Social response to emergency is an important mechanism for implementing and guaranteeing emergency management of major natural hazard-related disasters. Understanding how disaster information content affects social response to emergencies is helpful for managing risk communication and efficient disaster response. Based on the 2008 freezing-rain and snowstorm disasters in southern China, this study used Python to extract 7,857 case-related media reports and applied natural language processing for text analysis. It used three typical cases to identify and analyze disaster media report content and the relationship between these reports and the social response to the emergency. Eight categories of disaster response—such as prewarning and forecasting, announcements by the authorities, and social mobilization—appeared in the disaster information in the media, along with disaster impact information, that is, real-time disaster status. Disaster response information and an appropriate amount of disaster impact information played important roles in prewarning, disaster relief, public opinion guidance, and social stability maintenance and can serve important functions in communicating with all stakeholders of emergency management, assisting or influencing emergency departments or individuals in decision making, and eliminating “information islands.” Empathy caused the general public to become “disaster responders” through receiving information. Rumors and an excess of negative information may have a perverse amplification effect on public opinion and increase the unpredictability of the disaster situation and the risk of social crisis.

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Content-based user classifier to uncover information exchange in disaster-motivated networks

Cited by 5 publications

References 46 publications

Real-Time Prediction of Medical Demand and Mental Health Status in Ukraine under Russian Invasion Using Tweet Analysis

Real-Time Prediction of Medical Demand and Mental Health Status in Ukraine under Russian Invasion Using Tweet Analysis

Public Alert and Warning System Literature Review in the USA: Identifying Research Gaps and Lessons for Practice

Impact of Media Information on Social Response in Disasters: A Case Study of the Freezing-Rain and Snowstorm Disasters in Southern China in 2008

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