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The field of content analysis has rapidly advanced due to the integration of STEM methodologies in bibliometrics. This study aims to identify relevant trends observed in research on the utilization and development of biomarkers, based on metadata from Scopus. The STEM approach is expressed through a methodology structured in three stages: (1) retrieval and cleaning of information; (2) creation of a database where the abstracts have been segmented into two subsets using a Python script, based on the inclusion of phrases such as “biomarker/s is/are...” or “biomarker/s is/are not...”; and (3) STEM processing, focused on the analysis of eight word clouds organized into clusters, complemented by a results analysis using AI (artificial intelligence). The study demonstrates that STEM processing of large volumes of abstracts allows for the identification of patterns and the detection of evolutionary trends over time.

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A STEM Approach to Content Analysis Based on Abstracts from Scopus: The Case of Biomarkers

  • 会议论文

  • 发表日期：

    2025年

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  • Miguel Cruz-Ramírez,
  • Roberto Pérez-Rodríguez,
  • Luis Velázquez-Pérez

摘要

The field of content analysis has rapidly advanced due to the integration of STEM methodologies in bibliometrics. This study aims to identify relevant trends observed in research on the utilization and development of biomarkers, based on metadata from Scopus. The STEM approach is expressed through a methodology structured in three stages: (1) retrieval and cleaning of information; (2) creation of a database where the abstracts have been segmented into two subsets using a Python script, based on the inclusion of phrases such as “biomarker/s is/are...” or “biomarker/s is/are not...”; and (3) STEM processing, focused on the analysis of eight word clouds organized into clusters, complemented by a results analysis using AI (artificial intelligence). The study demonstrates that STEM processing of large volumes of abstracts allows for the identification of patterns and the detection of evolutionary trends over time.