Exploiting Social Networking and Mobile Data for Crisis Detection and Management

Doka, Katerina; Mytilinis, Ioannis; Giannakopoulos, Ioannis; Konstantinou, Ioannis; Tsitsigkos, Dimitrios; Terrovitis, Manolis; Koziris, Nectarios

doi:10.1007/978-3-319-67633-3_3

Cited by 3 publications

(4 citation statements)

References 6 publications

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“…Furthermore, the effectiveness of big data analytics is critical to ensuring that unexpected situations are deemed destructive and harmful in political, economic, societal, or environmental affairs involving security issues, particularly when they occur suddenly and unexpectedly, with little or no warning. As a result, in a crisis that causes social upheaval, it is critical to develop a crisis management plan quickly (Doka et al, 2017). While Watson et al (2017) provided findings from a case study of a big data survey, which support prior findings that big data can contribute to crisis response efforts by providing effective information for decision-makers.…”

Section: The Relationship Between Big Data Analytics and Crisis Manag...mentioning

confidence: 55%

“…Their case study demonstrates that the proposed knowledge management method improves situation awareness and decision making while dealing with a social security crisis. While Doka et al (2017) discovered a strong relationship between big data applications and crisis management, particularly crisis connected with riots in the community. Based on empirical data and previous research findings.…”

Section: The Relationship Between Big Data Analytics and Crisis Manag...mentioning

confidence: 99%

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The Effect of Big Data Analytics on Predictive Policing: The Mediation Role of Crisis Management

Alkhazraji,

Yahya

2024

RGSA

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Objective: The objective of this study is to evaluate the impact of big data analytics (BDA) on predictive policing, particularly examining the mediating role of crisis management in this relationship. Theoretical Framework: The research is anchored in the domain of big data analytics, focusing on its application within law enforcement for enhancing predictive policing capabilities. The study explores how crisis management serves as a linkage between data analytics and predictive policing practices. Method: The study gathered data from 450 individuals working across various police departments in Dubai, utilizing a questionnaire to collect responses. The analytical approach was based on Structural Equation Modeling, conducted using AMOS software. Results and Discussion: Findings from the research indicate that big data analytics significantly boosts predictive policing and crisis management. Importantly, crisis management was identified as a mediating factor between big data analytics and its efficacy in predictive policing. These results suggest that big data analytics not only directly enhances predictive policing but also improves it indirectly through effective crisis management. Research Implications: This study underscores the importance of integrating big data analytics into police operations to advance predictive policing capabilities. It highlights the dual benefits of big data analytics in both direct application and enhancement through crisis management processes. Originality/Value: This research contributes to the limited but growing body of literature on the application of big data analytics in predictive policing. It offers practical guidelines for police forces, especially within the UAE, to better harness big data for improving their operational effectiveness and crisis management strategies. The study also discusses broader implications for both practice and ongoing research in this evolving field.

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Section: The Relationship Between Big Data Analytics and Crisis Manag...mentioning

confidence: 55%

Section: The Relationship Between Big Data Analytics and Crisis Manag...mentioning

confidence: 99%

The Effect of Big Data Analytics on Predictive Policing: The Mediation Role of Crisis Management

Alkhazraji,

Yahya

2024

RGSA

View full text Add to dashboard Cite

show abstract

“…Their case study shows that the proposed knowledge management solution helps improve situational awareness and decision making when dealing with social security incidents. At the same time, Doka et al (2017) found a strong association between big data applications and crisis control, especially crises associated with the riot in the community. Based on the empirical results and findings from previous studies.…”

Section: The Relationship Between Big Data Analytics and Security Cri...mentioning

confidence: 96%

“…Many scholars are focusing on using big data to read trends and agendas in order to discover insights into big data using various data mining techniques in order to respond to unknown crises and future events (Park and Alenezi, 2018). Likewise, Doka et al (2017) found a strong association between big data analytics and crisis management, especially crises associated with the riot in the community which requires the interfere from the police.…”

Section: Hypotheses Testingmentioning

confidence: 99%

Developing an integrated framework for risk management in policing: crisis management using big data analytics as a case study

Albastaki,

Manap

2024

RGSA

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Objective: The study seeks to develop an integrated framework for enhancing risk management and crisis management in policing through the utilization of big data analytics, using the Dubai police force as a case study. Theoretical Framework: This research is grounded in the intersection of big data analytics and risk management within the field of policing, focusing on how data-driven approaches can innovate and improve security crisis management. Method: Data for the study was collected via questionnaires distributed to 450 police officers across all departments in Dubai. The analysis was conducted using AMOS software within a Structural Equation Modeling framework to assess the impact of big data analytics on police risk and crisis management. Results and Discussion: The results indicate that big data analytics significantly enhances risk management and crisis management in policing. It was found that police risk management serves as a mediating factor between big data analytics and security crisis management. These findings suggest that the application of big data can substantially improve knowledge and operational performance in police organizations. Research Implications: The study emphasizes the crucial role of big data analytics in revolutionizing police risk and crisis management processes. It highlights the potential for these technologies to provide substantial improvements in the efficiency and effectiveness of police operations. Originality/Value: This research is valuable as it provides empirical evidence of the benefits of big data analytics in the context of policing. It offers practical guidelines to police departments, particularly within the UAE, on leveraging big data to enhance their operational performance in managing risks and crises. The study contributes to the broader understanding of integrating advanced data analytics into public safety and emergency response strategies.

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Application of Big Data and Machine Learning Approaches to Improve Decision Making During Crises

Ali

2022

Advances in Electronic Government, Digital Divide, and Regional Development

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As an occurrence that jeopardises vital national interests or the basic needs of the populace, a crisis necessitates rapid decision-making and coordination between various departments and agencies in order to resolve it effectively. As a result, crisis and disaster management systems are necessary and critical. Crisis and disaster response systems are intricate, requiring numerous phases, techniques, and resources. These systems require useful and necessary data that can be used to make future decisions more effectively, such as historical and current data on crises. The use of machine learning and big data technologies to process data from crises and disasters has the potential to yield significant results in this area. The first section of this document discusses crisis management systems and available tools, such as big data and machine learning. Additionally, a machine learning and big data approach to crisis management systems were developed, which included a description and experiments, as well as a discussion of the findings and the field's future directions.

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Exploiting Social Networking and Mobile Data for Crisis Detection and Management

Cited by 3 publications

References 6 publications

The Effect of Big Data Analytics on Predictive Policing: The Mediation Role of Crisis Management

The Effect of Big Data Analytics on Predictive Policing: The Mediation Role of Crisis Management

Developing an integrated framework for risk management in policing: crisis management using big data analytics as a case study

Application of Big Data and Machine Learning Approaches to Improve Decision Making During Crises

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