Using lexical resources for detecting offensiveness in mexican spanish tweets

This work presents a description of our participation in subtasks 3 and 4 at MeOffendEs@IberLEF 2021 which consisted in classifying tweets as offensive or non-offensive in the OffendMEX corpus. For both subtasks, we proposed to use several Spanish lexicons which have a collection of words that have been weighted according to different criteria like affective, dimensional, and emotional values. In addition to them, structural values, word-embeddings and one-hot codification were taken into account. The scores of recall metric obtained in both subtasks was competitive comparing to both the baseline of the competition's and the other teams'.