In this paper, we address the importance of classification and social media mining of human emotions. We compared different theories about basic emotions and the application of emotion theory in practice. Based on Plutchik's classification, we suggest creating a specialized lexicon with terms and phrases to identify emotions for research of general attitudes towards mobile learning in social media. The approach can also be applied to other areas of scientific knowledge that aim to explore the emotional attitudes of users in social media. It is based on the Natural Language Processing and more specifically uses text mining classification algorithms. For test purposes, we have retrieved a number of tweets on users' attitudes towards mobile learning.
This paper is included in the program of DIGILIENCE 2019 and will be published in the post-conference volume. In the meantime, you can download the presentation using the link above.