Author(s)

Sayan Roy^1,*, Hriddhiman Basu²

Affiliation(s)

¹ Indian Institute of Management Calcutta, India.

² Indian Institute of Management Mumbai, India.

Corresponding Author

Sayan Roy

ABSTRACT

In this study, word dynamics, co-occurring phrases, and keyword frequency in the area of androgenetic alopecia were thoroughly analysed during a ten-year period. The study tracks changes in word usage, frequency, and context and identifies variations in the distribution and usage patterns of keywords, subjects, and co-occurring phrases using natural language processing techniques and graph theory-based approaches. The research reveals hidden linkages and patterns between diverse ideas, shedding light on the co-occurrence patterns of numerous phrases in the literature on androgenetic alopecia. The study emphasises the value of clearly visualising and disseminating findings to a large audience. In order to communicate the findings of the 10-year trend analysis to patrons, legislatures, and other pertinent audiences, data visualisation tools, infographics, and reports are used. This makes sure that the results are useful, effective, and easily accessible so that they can guide the creation of policies and decisions pertaining to androgenetic alopecia. The results of this study may have substantial ramifications for academics, medical professionals, policymakers, and other industry participants. The research can lead future research paths, prioritise research areas, and suggest areas that require additional examination by highlighting key research challenges and pointing out gaps in the study of androgenetic alopecia. Identifying emergent study issues, analysing the changing patterns in the area, and establishing research strategies can all benefit from an analysis of word dynamics and correlations among terms. The results reveal hidden relationships and patterns, advance knowledge of the research environment in this area, and influence androgenetic alopecia research objectives and policies.

KEYWORDS

Hair loss; Androgenetic alopecia; Bibliometric; Text citation; Data visualizations

CITE THIS PAPER

Sayan Roy, Hriddhiman Basu. Beyond hair loss: exploring the evolution of androgenetic alopecia research based on text mining and bibliometrics. World Journal of Management Science. 2024, 2(3): 1-9. DOI: 10.61784/wms3010.

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