Big data and sentiment analysis to highlight decision behaviours: a case study for student population

Orlando Troisi, Mara Grimaldi, Francesca Loia and Gennaro Maione

Behaviour and Information Technology, 2018, vol. 37, issue 10-11, 1111-1128

Abstract: Starting from the assumption that the factors orienting University choice are heterogeneous and multidimensional, the study explores student’s motivations in higher education. To this aim, a big data analysis has been performed through ‘TalkWalker’, a tool based on the algorithms developed in the context of Social Data Intelligence, which allows understanding the sentiment of a group of people regarding a specific theme. The data have been extracted by drawing on published posts from anywhere in the world over a 12-month period from many online sources. According to the findings, the main variable capable of influencing the choice of University is training offer, followed by physical structure, work opportunities, prestige, affordability, communication, organisation, environmental sustainability. The study establishes an innovative research agenda for further studies by proposing the elaboration of a systems and process-based view for higher education. However, it presents the limitation of the superficial investigation, determined by the analysis of a large amount of data. Therefore, for future research, it might be appropriate to apply a different technique to realise a comparison and to check whether the size of the considered sample and the depth of the analysis technique can affect the results and the consequent considerations.

Date: 2018
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DOI: 10.1080/0144929X.2018.1502355

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