Sentiment analysis on educational datasets: a comparative evaluation of commercial tools
Foteini S. Dolianiti, Dimitrios Iakovakis, Sofia B. Dias, Sofia J. Hadjileontiadou, José Alves Diniz, Georgia Natsiou, Melpomeni Tsitouridou, Panagiotis D. Bamidis, Leontios J. Hadjileontiadis · 2019
Sentiment analysis systems have been gaining increasing popularity for extracting information regarding students' affective state. Developing such systems from scratch is a challenging task, thus, many studies employ commercial, general-purpose tools that are not domain-specific. The aim of the present work is to comparatively evaluate the performance of five well-known commercial/academic sentiment analysis tools on two educational datasets and contrast it with the performance of educational domain-specific tools, at document and sentence level. Findings suggest that: a) different tools work better for specific datasets and analysis levels, b) depending on the dataset, a general-purpose tool might be a viable solution, and c) any method, domain-specific or general-purpose one, should be evaluated before employed.