EXPLORATION OF THE THEMATIC CLUSTERING AND COLLABORATION OPPORTUNITIES IN KAZAKHSTANI RESEARCH

Authors

DOI:

https://doi.org/10.37943/17ALVR8114

Keywords:

data preprocessing, natural language processing , thematic clustering , research abstracts

Abstract

In today's academic environment, the rapid growth of research publications calls for advanced methods to organize and understand the extensive collections of academic work. This study aims to systematically categorize a substantial number of research paper abstracts from Kazakhstani institutions, focusing on identifying key themes and potential interdisciplinary collaboration opportunities. The dataset includes 13,356 abstracts from the Scopus database, covering a wide range of academic fields. The methodology of this research goes beyond traditional hand-done analysis by using advanced text analysis tools to organize the text data efficiently. This initial phase is crucial for summarizing each abstract's core content. The next steps of the analysis use this organized data to find and group similar thematic areas, considering the complex and multi-dimensional nature of academic research topics. The results reveal a diverse array of research themes, highlighting the dynamic academic contributions from Kazakhstan. Significant areas such as environmental science, technological advancements, linguistics, and cultural studies are among the prominent clusters identified. These insights not only provide an overview of current research directions but also highlight the potential for cross-disciplinary partnerships. Moreover, the findings have important implications for decision-makers, scholars, and educational institutions by illuminating key research areas and collaborative possibilities. This thematic overview acts as a guide for shaping research policies, fostering academic connections, and efficiently distributing resources within the scholarly community. Ultimately, this study adds to the academic conversation by offering a way to navigate and utilize the wealth of information in scientific literature, promoting a more collaborative and integrated research environment.

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Published

2024-03-31

How to Cite

Biloshchytskyi, A., Shamgunova, . M. ., & Biloshchytska , S. . (2024). EXPLORATION OF THE THEMATIC CLUSTERING AND COLLABORATION OPPORTUNITIES IN KAZAKHSTANI RESEARCH. Scientific Journal of Astana IT University, 17(17), 106–121. https://doi.org/10.37943/17ALVR8114

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Section

Information Technologies
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