  Social media are an essential source of meaningful data that can be used in
different tasks such as sentiment analysis and emotion recognition. Mostly,
these tasks are solved with deep learning methods. Due to the fuzzy nature of
textual data, we consider using classification methods based on fuzzy rough
sets. Specifically, we develop an approach for the SemEval-2018 emotion
detection task, based on the fuzzy rough nearest neighbour (FRNN) classifier
enhanced with ordered weighted average (OWA) operators. We use tuned ensembles
of FRNN--OWA models based on different text embedding methods. Our results are
competitive with the best SemEval solutions based on more complicated deep
learning methods.
