The ever-growing phenomenon of scholarly documents offers new perspective for computational analysis of academic writing, going beyond traditional citation metrics. Therefore, this study uses a detailed text mining approach to analyze full text journal articles written by Professor KP Singh, a renowned personality in field of Library and Information Science in India. His extensive contributions to national and international journals provide a substantial and thematically rich corpus for computational scholarly analysis. However, the present study only aims to conduct a comprehensive text mining of 105 full text journal articles written by Professor KP Singh. The complex nature of his research requires using combined exhaustive methods to find hidden themes and connection. Through full text analysis, this study shows a clear intellectual text mining method marked by strong ties to specific fields, a variety of methods and consistent themes. Topic modeling uncovers distinct but related research areas, whereas similarity and cluster analysis reveal organized semantic groups among the publications. Co-word network mapping emphasizes the importance and integration of his work within the Library and Information Science field. These findings not only highlight the depth and diversity of Professor Singh’s research path but also show the usefulness of full text mining for detailed author level academic analysis.
Sharma et al. (Thu,) studied this question.