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Taking a new perspective
(2016)
Network analysis has attracted significant attention when researching the phenomenon of transnational terrorism, particularly Al Qaeda. While many scholars have made valuable contributions to mapping Al Qaeda, several problems remain due to a lack of data and the omission of data provided by international organizations such as the UN. Thus, this article applies a social network analysis and subsequent mappings of the data gleaned from the Security Council's consolidated sanctions list, and asks what they can demonstrate about the structure and organizational characteristics of Al Qaeda. The study maps the Al Qaeda network on a large scale using a newly compiled data set. The analysis reveals that the Al Qaeda network consists of several hundred individual and group nodes connecting almost all over the globe. Several major nodes are crucial for the network structure, while simultaneously many other nodes only weakly and foremost regionally connect to the network. The article concludes that the findings tie in well to the latest research pointing to local and simultaneously global elements of Al Qaeda, and that the new data is a valuable source for further analyses, potentially in combination with other data.
The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research.
The field of healthcare is characterized by constant innovation, with gender-specific medicine emerging as a new subfield that addresses sex and gender disparities in clinical manifestations, outcomes, treatment, and prevention of disease. Despite its importance, the adoption of gender-specific medicine remains understudied, posing potential risks to patient outcomes due to a lack of awareness of the topic. Building on the Innovation Decision Process Theory, this study examines the spread of information about gender-specific medicine in online networks. The study applies social network analysis to a Twitter dataset reflecting online discussions about the topic to gain insights into its adoption by health professionals and patients online. Results show that the network has a community structure with limited information exchange between sub-communities and that mainly medical experts dominate the discussion. The findings suggest that the adoption of gender-specific medicine might be in its early stages, focused on knowledge exchange. Understanding the diffusion of gender-specific medicine among medical professionals and patients may facilitate its adoption and ultimately improve health outcomes.