OASIcs.SLATE.2018.19.pdf
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Predicting Performance Problems Through Emotional Analysis (Short Paper)
Authors
Ricardo Martins 
,
José João Almeida ,
Pedro Rangel Henriques ,
Paulo Novais
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Volume:
7th Symposium on Languages, Applications and Technologies (SLATE 2018)
Series: Open Access Series in Informatics (OASIcs)
Conference: Symposium on Languages, Applications and Technologies (SLATE) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2018-07-13
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Author Details
- Centro Algoritmi / Departamento de Informática, Universidade do Minho, Campus de Gualtar, Braga, Portugal
- Centro Algoritmi / Departamento de Informática, Universidade do Minho, Campus de Gualtar, Braga, Portugal
- Centro Algoritmi / Departamento de Informática, Universidade do Minho, Campus de Gualtar, Braga, Portugal
Cite AsGet BibTex
Ricardo Martins, José João Almeida, Pedro Rangel Henriques, and Paulo Novais. Predicting Performance Problems Through Emotional Analysis (Short Paper). In 7th Symposium on Languages, Applications and Technologies (SLATE 2018). Open Access Series in Informatics (OASIcs), Volume 62, pp. 19:1-19:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/OASIcs.SLATE.2018.19
https://doi.org/10.4230/OASIcs.SLATE.2018.19
Abstract
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.
Subject Classification
ACM Subject Classification
- Computing methodologies → Natural language processing
Keywords
- emotion analysis
- machine learning
- natural processing language
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References
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