This article addresses the expanding presence of content analysis in bibliometric studies. The Journal of Nanoparticle Research publishes bibliometric articles for insights regarding research, industrial, and societal trends centering on nanotechnology. Characteristic of bibliometrics is its reliance on network analysis, which is the basis for claiming that earlier-in-time documents influence later ones, i.e., for drawing causal inferences. Bibliometric techniques employed in the Journal’s articles (bibliographic coupling, co-citation, word co-occurrence, and main path analyses) are examined and comparisons made to the methodology expected of review articles authored by subject matter experts. The potential for subject matter experts to change their literature practices using open, noncommercial search technology and the increasing availability of content analysis techniques, such as large language models, are recurring themes. Major focal points are as follows: delineating research communities using keywords or alternatives, ensuring that commercial and marketplace characteristics align with search criteria when examining patents, and balancing the individual’s informal use of search technology and artificial intelligence with the formal, statistical analyses expected with published bibliometric articles.
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Frederick C. Klaessig (2026) studied this question.
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