The article presents the authors' methodology for the study of Chinese Marxism and its ideological and philosophical principles, as well as the potential impact of this direction on the humanitarian development of modern Ukrainian society. The authors substantiated the integral methodological task, which consists of the implementation of a comparative typological analysis of the philosophical foundations of Sinicized Marxism with modern European Marxist philosophical schools and "Soviet" Marxism. The article confirms that a more effective approach in the study of the socio-cultural implications of modern Sinicized Marxism is (1) the study of the process of "Sinicization" of Marxism; (2) study and evaluation of existing and potential strategies for the implementation of Sinicized Marxism in the practices of intercultural communication (One Belt, One Road Initiative) and the education system; (3) analysis of the philosophical and ideological content and practical goals of the humanitarian part of China's international One Belt, One Road Initiative, development of a methodology for assessing the benefits and risks of its implementation for European countries and Ukraine.
The demand for the creation of information systems that simplifies and accelerates work has greatly increased in the context of the rapidinformatization of society and all its branches. It provokes the emergence of more and more companies involved in the development of softwareproducts and information systems in general. In order to ensure the systematization, processing and use of this knowledge, knowledge managementsystems are used. One of the main tasks of IT companies is continuous training of personnel. This requires export of the content from the company'sknowledge management system to the learning management system. The main goal of the research is to choose an algorithm that allows solving theproblem of marking up the text of articles close to those used in knowledge management systems of IT companies. To achieve this goal, it is necessaryto compare various topic segmentation methods on a dataset with a computer science texts. Inspec is one such dataset used for keyword extraction andin this research it has been adapted to the structure of the datasets used for the topic segmentation problem. The TextTiling and TextSeg methods wereused for comparison on some well-known data science metrics and specific metrics that relate to the topic segmentation problem. A new generalizedmetric was also introduced to compare the results for the topic segmentation problem. All software implementations of the algorithms were written inPython programming language and represent a set of interrelated functions. Results were obtained showing the advantages of the Text Seg method incomparison with TextTiling when compared using classical data science metrics and special metrics developed for the topic segmentation task. Fromall the metrics, including the introduced one it can be concluded that the TextSeg algorithm performs better than the TextTiling algorithm on theadapted Inspec test data set.
The article examines a number of issues related to the specifics of information dissemination under the conditions of communicative practice of both an individual level and the functioning of mass media. The main attention is paid to the issue of the deliberate spread of disinformation. In this context, the phenomenon of "hybrid war" and the place of the information component in it, the issue of using narratives as an effective means of mass information damage, and the specifics of the process of "devaluation of the word". The need to develop mechanisms to counteract the phenomena of "abuse of freedom of speech" and "simulative democracy" to ensure the survival and sustainable development of democratic societies is substantiated.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.