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Impact for whom? Mapping the users of public research with lexicon-based text mining

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  • Andrea Bonaccorsi

    (University of Pisa)

  • Filippo Chiarello

    (University of Pisa)

  • Gualtiero Fantoni

    (University of Pisa)

Abstract

We contribute to the debate on societal impact of SSH by developing a methodology that allows a fine-grained observation of social groups that make use, directly or indirectly, of the results of research. We develop a lexicon of users with 76,857 entries, which saturates the semantic field of social groups of users and allows normalization. We use the lexicon in order to filter text structures in the 6637 impact case studies collected under the Research Excellence Framework in the UK. We then follow the steps recommended by Börner et al. (Annu Rev Inf Sci Technol 37:179–255, 2003) to build up visual maps of science, using co-occurrence of words describing users of research. We explore the properties of this novel kind of maps, in which science is seen from the perspective of research users.

Suggested Citation

  • Andrea Bonaccorsi & Filippo Chiarello & Gualtiero Fantoni, 2021. "Impact for whom? Mapping the users of public research with lexicon-based text mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1745-1774, February.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:2:d:10.1007_s11192-020-03803-z
    DOI: 10.1007/s11192-020-03803-z
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    1. Mauricio Marrone & Sascha Lemke & Lutz M. Kolbe, 2022. "Entity linking systems for literature reviews," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3857-3878, July.
    2. Yaqub, Ohid & Malkov, Dmitry & Siepel, Josh, 2022. "How unpredictable is research impact? Evidence from the UK’s Research Excellence Framework," SocArXiv qw873, Center for Open Science.
    3. Chiarello, Filippo & Giordano, Vito & Spada, Irene & Barandoni, Simone & Fantoni, Gualtiero, 2024. "Future applications of generative large language models: A data-driven case study on ChatGPT," Technovation, Elsevier, vol. 133(C).

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