The aim of this research is to build a methodological framework for the identification of users engaging with scholarly productions on Twitter by focusing on their Twitter bios. Based on a corpus of 4 719 research papers, 41 019 tweets and 21 965 unique users engaging with climate change research from 2015 and 2016, we are developing a codebook, by manual and semi-automatic coding of these bios, for the identification for seven types of accounts – 1) Faculty members and students; 2) Institutions and organizations; 3) Bots and automated accounts; 4) Journals and publishers; 5) Communicators; 6) Professionals; 7) Personal. As this work focus on public engagement with science, our focus is on the identification of lay users, defined as those using only Personal expressions in their bios. Preliminary results based on the first iteration of the codebook lead the categorization of 12 415 accounts, 5 949 of them including Personal expressions. However, results also indicate a significant overlap with other categories, especially Faculty members and students (n = 1 782). Future work will focus on refining the codebook for further analysis and manual coding to more accurately measure the precision of these results.
Ce contenu a été mis à jour le 5 janvier 2021 à 13 h 25 min.