Analysis of Research Trends in Indian Computer Science Scholarly Communication: A Methodological Perspective with Python
Author(s): Ashoka R. & N.S. Harinarayana
Abstract - This study investigates research trends in the Indian computer science journal over a ten-year period (2011- 2020) using keyword-based analysis across title, abstract, and author-supplied metadata. Since the selected journals were not uniformly indexed in an international database, the study employed a combined approach of manual review and automated data extraction to ensure comprehensive coverage. Keywords were lemmatized and filtered utilizing YAKE score and frequency threshold, thereafter analysed through TF-IDF vectorization, cosine similarity, and hierarchical clustering. The top 25 semantically relevant keywords were extracted from each source. Thematic dendrograms indicated a constant tendency in wireless sensor networks, neural networks, machine learning, and cybersecurity. Hypothesis testing revealed no substantial disparity in term distribution within the metadata layer, suggesting theme congruence. The research advances metadata standards and provides a reproducible framework for trend analysis and vocabulary enhancement in scholarly communication.
Keywords - Keyword Analysis, Research Trends, Computer Science Journal, YAKE, Semantic Clustering.
DOI URL: https://doi.org/10.26761/ijrls.11.2.2025.1882
Cite This Article As: Ashoka, R. & Harinarayana, N.S. (2025) Analysis of Research Trends in Indian Computer Science Scholarly Communication: A Methodological Perspective with Python. International Journal of Research in Library Science (IJRLS), 11(2) 140-150. www.ijrls.in
Copyright © 2025 Author(s) retains the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0.
Paper ID: IJRLS-1882 Page: 140-150 Publication Date: 16 May 2025