scholarly journals Toward a Stakeholder Perspective on Safety Risk Factors of Metro Construction: A Social Network Analysis

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ying Lu ◽  
Yu Zhang
Keyword(s):  
Risk Factors ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Government Regulation ◽  
Rapid Development ◽  
Construction Site ◽  
Safety Risk ◽  
Stakeholder Perspective ◽  
Bad Weather

The rapid development of the metro has greatly relieved the traffic pressure on the urban ground system, but the frequency of metro construction accidents is also increasing year by year. Due to the complex construction process of the metro, once an accident occurs, casualties and property damage are extremely serious. The safety risk factors triggered by different stakeholders were the primary cause of accidents during the metro construction phase. This paper builts a social analysis network of safety risk factors in metro construction from a stakeholder’s perspective. Based on 42 accident cases and related literature, 6 stakeholders and 25 safety risk factors were identified and the relationships between stakeholders and safety risk factors were also determined. Through the application of social network analysis, a social network of safety risk factors in metro construction was constructed, and quantitative analysis was carried out based on density, degree centrality, betweenness centrality, and cohesive subgroup. The results showed that the key safety risk factors in the construction phase of the metro were in action of the contractor’s construction site managers, lack of safety protection at the construction site, insufficient detailed survey and design information provided by the designer, unfavorable government regulation, and bad weather. Moreover, the results of 20 cohesive subgroups illustrated the interrelationship between safety risk factors. S1H2 (“violations by operatives” related to contractor) and S1H4 (“lack of safety precautions” related to contractor) and S5H5 (“ineffective supervision” related to supervisor) both belonged to subgroup G1, which means that there is a high probability that these three safety risk factors would occur simultaneously. This paper provided a basis to improve the level of safety risk management and control from the stakeholder’s perspective.

scholarly journals Risk factors for Clonorchis sinensis infection transmission in humans in northern Vietnam: A descriptive and social network analysis study

2017 ◽  
Vol 66 (2) ◽  
pp. 74-82 ◽  
Author(s):  
Hoang Quang Vinh ◽  
Waraphon Phimpraphai ◽  
Sirikachorn Tangkawattana ◽  
John F. Smith ◽  
Sasithorn Kaewkes ◽  
...  
Keyword(s):  
Risk Factors ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Clonorchis Sinensis ◽  
Infection Transmission ◽  
Analysis Study ◽  
Northern Vietnam

scholarly journals Stakeholder-Associated Risks and Their Interactions in PPP Projects: Social Network Analysis of a Water Purification and Sewage Treatment Project in China

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Mingzhu Yang ◽  
Haitao Chen ◽  
Yongshun Xu
Keyword(s):  
Risk Factors ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Local Governments ◽  
Risk Sharing ◽  
Sewage Treatment ◽  
Project Managers ◽  
Individual Level ◽  
The Individual

As a result of complex contractual relationships, multiple stakeholders with different interests are involved in public-private partnership (PPP) projects. Compared to traditional models, PPP projects have more uncertainty. This study integrated stakeholders and risk factors in PPP projects from a network perspective to better determine how to control risks. Using social network analysis (SNA), a case study was conducted to identify the critical risk factors, and mitigation actions are proposed. The results indicated that, compared to other stakeholders, local governments play the most important role in PPP projects. Managers should therefore pay more attention to political and legal risk factors and develop reasonable risk-sharing plans. This study expands PPP risk research from the individual level to the network level and provides a visualized, innovative research paradigm for PPP risk analysis. The results can also be used by project managers for decision-making, risk management, and other processes, thus helping to achieve the sustainable management of PPP projects.

scholarly journals Descriptive analysis of a tuberculosis outbreak from a northern Saskatchewan First Nations community—December 2018 to May 2019

2021 ◽  
Vol 47 (11) ◽  
pp. 479-484
Author(s):  
Nnamdi Ndubuka ◽  
Braeden Klaver ◽  
Sabyasachi Gupta ◽  
Shree Lamichhane ◽  
Leslie Brooks ◽  
...  
Keyword(s):  
Risk Factors ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
First Nations ◽  
Descriptive Analysis ◽  
Outbreak Investigation ◽  
Active Case ◽  
Contact Investigation ◽  
Northern Saskatchewan

Background: The tuberculosis (TB) incidence rate for northern Saskatchewan First Nations on-reserve is 1.5 higher than the national average. In December 2018 a member of one of these communities was diagnosed with 4+ smear-positive TB, spurring an outbreak investigation. Objectives: To describe the public health response to TB outbreak investigation and highlight the risk factors associated with TB transmission in northern Saskatchewan; and to highlight the relevance of social network contact investigation tool in outbreak management. Methods: Descriptive analysis included active TB cases and latent TB infection (LTBI) cases linked by contact investigation to the index case. Data were collected from active TB case files. Statistical analyses were performed and social network analysis conducted using household locations as points of contact between cases. Results: A total of eight active TB cases and 41 LTBI cases were identified as part of the outbreak between December 2018 and May 2019. Half of the cases (4/8) were 25 to 34 years old, and five were smear negative. One-third of the people with LTBI were 15 to 24 years old, and about a half tested positive to the new tuberculin skin test (TST). The commonly reported risk factors for TB and LTBI cases were alcohol use, cigarette use, marijuana use, previous TB infection and homelessness. Social network analysis indicated a relationship between increased node centrality and becoming an active case. Conclusion: Real-time social network contact investigation used in active-case finding was very successful in identifying cases, and enhanced nursing support, mobile clinics and mobile X-ray worked well as a means of confirming cases and offering treatment. TB outbreaks in northern Saskatchewan First Nations on-reserve communities are facilitated by population-specific factors. Efforts to implement context-specific interventions are paramount in managing TB outbreaks and preventing future transmission.

scholarly journals HackerRank: Identifying key hackers in underground forums

2021 ◽  
Vol 17 (5) ◽  
pp. 155014772110151
Author(s):  
Cheng Huang ◽  
Yongyan Guo ◽  
Wenbo Guo ◽  
Ying Li
Keyword(s):  
Content Analysis ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Rapid Development ◽  
Manual Analysis ◽  
Threat Intelligence ◽  
Comprehensive Evaluations ◽  
Cyber Threat Intelligence ◽  
Surface Web

With the rapid development of the Internet, cybersecurity situation is becoming more and more complex. At present, surface web and dark web contain numerous underground forums or markets, which play an important role in cybercrime ecosystem. Therefore, cybersecurity researchers usually focus on hacker-centered research on cybercrime, trying to find key hackers and extract credible cyber threat intelligence from them. The data scale of underground forums is tremendous and key hackers only represent a small fraction of underground forum users. It takes a lot of time as well as expertise to manually analyze key hackers. Therefore, it is necessary to propose a method or tool to automatically analyze underground forums and identify key hackers involved. In this work, we present HackerRank, an automatic method for identifying key hackers. HackerRank combines the advantages of content analysis and social network analysis. First, comprehensive evaluations and topic preferences are extracted separately using content analysis. Then, it uses an improved Topic-specific PageRank to combine the results of content analysis with social network analysis. Finally, HackerRank obtains users’ ranking, with higher-ranked users being considered as key hackers. To demonstrate the validity of proposed method, we applied HackerRank to five different underground forums separately. Compared to using social network analysis and content analysis alone, HackerRank increases the coverage rate of five underground forums by 3.14% and 16.19% on average. In addition, we performed a manual analysis of identified key hackers. The results prove that the method is effective in identifying key hackers in underground forums.

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