2026-07-22T00:15:23Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:9277 2024-03-06T10:30:20Z ddc:004 open_access

Predicting Performance Problems Through Emotional Analysis (Short Paper) Martins, Ricardo Almeida, José João Henriques, Pedro Rangel Novais, Paulo emotion analysis machine learning natural processing language In the cartoons, every time a character is nervous he/she begins to count to ten to keep calm. This is a technique, among hundreds, that helps to control the emotional state. However, what would be the impact if the emotions would not be controlled? Are the emotions important in terms of impairing the ability to perform tasks correctly? Using a case study of typing text, this paper is about a process to predict the number of writing errors from a person based on the emotional state and some characteristics of the writing process. Using preprocessing techniques, lexicon-based approaches and machine learning, we achieved a percentage of 80% of correct values, when considering the emotional profile on the writing style. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ricardo Martins and José João Almeida and Pedro Rangel Henriques and Paulo Novais 2018 Is Part Of OASIcs, Volume 62, 7th Symposium on Languages, Applications and Technologies (SLATE 2018) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.SLATE.2018.19 urn:nbn:de:0030-drops-92773 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2018.19 eng https://creativecommons.org/licenses/by/3.0/legalcode