scholarly journals Oil Spill Response Policies to Bridge the Perception Gap between the Government and the Public: A Social Big Data Analysis

2020 ◽  
Vol 8 (5) ◽  
pp. 335 ◽  
Author(s):  
Joungyoon Chun ◽  
Jeong-Hwan Oh ◽  
Choong-Ki Kim

Oil spills cause socioeconomic and ecological damage to the marine environment and local communities. Implementing policies to effectively cope with such incidents is a challenging task due to the negative public perceptions about governmental responses. Using social big data, this study analyzed such negative perceptions in South Korea and the factors influencing them. The findings indicate that the public pays relatively little attention to oil spills but expresses serious concerns about the economic and ecological damage and the health and safety of volunteers and local residents. To improve public perception of oil spills, response strategies should aim to (1) analyze it using social big data to reduce the gap between governmental and public spheres, (2) release timely and accurate information to resolve civil distrust and dissatisfaction, (3) minimize direct damage to local communities and ecosystems affected by oil spills, and (4) reduce the impact on volunteers’ and local residents’ health and safety. Furthermore, through a multidisciplinary approach that combines social big data analysis methods with marine scientific research, it can contribute to creating a disaster response policy tailored to policy consumers.

2020 ◽  
Vol 25 (2) ◽  
pp. 18-30
Author(s):  
Seung Wook Oh ◽  
Jin-Wook Han ◽  
Min Soo Kim

2016 ◽  
Vol 24 ◽  
Author(s):  
Jessica Heesen

Big data-analysis is linked to the expectation to provide a general image of socially relevant topics and processes. Similar to this, the idea of the public sphere involves being representative of all citizens and of important topics and problems. This contribution, on one side, aims to explain how a normative concept of the public sphere could be infiltrated by big data. On the other, it will discuss how participative processes and common wealth can profit from a thorough use of big data analysis. As important parts of the argument, two concepts will be introduced: the numerical public (as a public that is constituted by machine-communication) and total politicisation (as a loss of negative freedom of expression).


Author(s):  
Weng-Kun Liu ◽  
Chia-Chun Yen

With the advances in industry and commerce, passengers have become more accepting of environmental sustainability issues; thus, more people now choose to travel by bus. Government administration constitutes an important part of bus transportation services as the government gives the right-of-way to transportation companies allowing them to provide services. When these services are of poor quality, passengers may lodge complaints. The increase in consumer awareness and developments in wireless communication technologies have made it possible for passengers to easily and immediately submit complaints about transportation companies to government institutions, which has brought drastic changes to the supply-demand chain comprised of the public sector, transportation companies, and passengers. This study proposed the use of big data analysis technology including systematized case assignment and data visualization to improve management processes in the public sector and optimize customer complaint services. Taichung City, Taiwan was selected as the research area. There, the customer complaint management process in public sector was improved, effectively solving such issues as station-skipping, allowing the public sector to fully grasp the service level of transportation companies, improving the sustainability of bus operations, and supporting the sustainable development of the public sector-transportation company-passenger supply chain.


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