The study proposes a text mining procedure useful for comparing the documents’ symbolic-cultural categories. In particular, Emotional Text Mining was used to study the cultural differences of digital development in higher education among countries through the analysis of the country partners’ report of the Erasmus+Project ECOLHE (Empower Competences for Onlife Learning in Higher Education), to identify the symbolic-cultural categories and the representations of digital development. In the European projects, there is often a phase in which the results are compared with qualitative, quantitative, or mixed methods. Among the various elements that organize the comparison, an important component is the cultural dimension, since it organizes social actors’ practices, which is often carried out with qualitative methods. However, in line with the literature, this dimension is detectable through text mining methods since it determines the choice and association of the words used to organize communication. Results have important implications for the identification of digital culture development indicators starting from texts, an aspect that could be considered relevant for policy makers in the context of Erasmus+ projects.

Comparative Analysis of National Reports: The Case of the Erasmus+ ECOLHE Project

Greco, Francesca
2024-01-01

Abstract

The study proposes a text mining procedure useful for comparing the documents’ symbolic-cultural categories. In particular, Emotional Text Mining was used to study the cultural differences of digital development in higher education among countries through the analysis of the country partners’ report of the Erasmus+Project ECOLHE (Empower Competences for Onlife Learning in Higher Education), to identify the symbolic-cultural categories and the representations of digital development. In the European projects, there is often a phase in which the results are compared with qualitative, quantitative, or mixed methods. Among the various elements that organize the comparison, an important component is the cultural dimension, since it organizes social actors’ practices, which is often carried out with qualitative methods. However, in line with the literature, this dimension is detectable through text mining methods since it determines the choice and association of the words used to organize communication. Results have important implications for the identification of digital culture development indicators starting from texts, an aspect that could be considered relevant for policy makers in the context of Erasmus+ projects.
2024
9783031559167
9783031559174
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1293276
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