Malaterre, C et Lareau, F
(2023).
« Visualizing Hidden Communities of Interest: A Preliminary Analysis of Topic-based Social Networks in Astrobiology », dans 19th International Conference on Scientometrics & Informetrics, ISSI 2023 Proceedings. (19th International Conference on Scientometrics & Informetrics, ISSI 2023 Proceedings. 2-5 juillet 2023, Bloomington, États-Unis., 2023-07)
Bloomington, États-Unis., pp. 291-297.
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Résumé
Author networks in science often rely on citation analyses. In such cases, as in others, network interpretation usually depends on supplementary data, notably about authors’ research domains when disciplinary interpretations are sought. More general social networks also face similar interpretation challenges as to the semantic content specificities of their members. In this research-in-progress, we propose to infer author networks not from citationbanalyses but from a topic-model of published works. Such author networks reveal, as we call them, “hidden communities of interest” (HCoI’s) whose semantic content can easily be interpreted by means of their associated topics in the model. We use an astrobiology corpus of full-text articles (N=3,698) to illustrate the approach. Having conducted an LDA topic-model on all publications, we identify the underlying communities of authors by measuring author correlations in terms of topic distributions. Adding publication dates makes it possible to examine HCoI evolution over time, thereby providing a diachronic perspective on the emergence of this recent domain of scientific investigation over the past five decades.
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