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It is widely recognised that science in Africa will benefit from international research collaboration (IRC), and therefore studies have been done on IRC in Africa (hereafter: Africa-related IRC research). However, there is no information on the development of Africa-related IRC research, the geographical location of the scientists interested in the topic, the visibility of the literature and the themes researched. This information makes it possible to understand relevant aspects in the context of IRC in Africa, which are useful for identifying IRC strengths, weaknesses and opportunities. It also allows paving the way for future research on this topic. Using discipline–specific terms, bibliometric, and thematic analysis, I collected the literature on Africa-related IRC research indexed in the Web of Science Core Collection (WoS). The results showed that the number of publications on the topic has increased, few African countries have researched the topic, a third of the publications were written exclusively by African scientists, and the topic has high visibility. The panoply of publications revealed that patterns, driving factors, effects, networks, asymmetries, and policies concerning IRC were the main themes researched.
相似文献Modern metrics for evaluating agreement coefficients between the experimental results and expert opinion are compared, and the possibility of using these metrics in experimental research in automatic text processing by machine learning methods is assessed. The choice of Cohen’s kappa coefficient as a measure of expert opinion agreement in the NLP and Text Mining problems is justified. An example of using Cohen’s kappa coefficient for evaluating the level of agreement between the opinion of an expert and the results of ML classification and the measure of agreement of expert opinions in the alignment of sentences of the Kazakh-Russian parallel corpus is given. Based on this analysis, it is proved that Cohen’s kappa coefficient is one of the best statistical methods for determining the level of agreement in experimental studies due to its ease of use, computing simplicity, and high accuracy of the results.
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