The Possibilities of Classification of Emotional States Based on User Behavioral Characteristics
The classification of user's emotions based on their behavioral characteristic, namely their keyboard typing and mouse usage pattern is an effective and non-invasive way of gathering user's data without imposing any limitations on their ability to perform tasks. To gather data for the clas...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Universidad Internacional de La Rioja (UNIR)
2021-03-01
|
Series: | International Journal of Interactive Multimedia and Artificial Intelligence |
Subjects: | |
Online Access: | https://www.ijimai.org/journal/bibcite/reference/2850 |
id |
doaj-d86532ca1826483f9ca20e893663e608 |
---|---|
record_format |
Article |
spelling |
doaj-d86532ca1826483f9ca20e893663e6082021-03-03T22:41:42ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16601989-16602021-03-01649710410.9781/ijimai.2020.11.010ijimai.2020.11.010The Possibilities of Classification of Emotional States Based on User Behavioral CharacteristicsMartin MagdinD. DržíkJ. ReichelS KoprdaThe classification of user's emotions based on their behavioral characteristic, namely their keyboard typing and mouse usage pattern is an effective and non-invasive way of gathering user's data without imposing any limitations on their ability to perform tasks. To gather data for the classifier we used an application, the Emotnizer, which we had developed for this purpose. The output of the classification is categorized into 4 emotional categories from Russel's complex circular model - happiness, anger, sadness and the state of relaxation. The sample of the reference database consisted of 50 students. Multiple regression analyses gave us a model, that allowed us to predict the valence and arousal of the subject based on the input from the keyboard and mouse. Upon re-testing with another test group of 50 students and processing the data we found out our Emotnizer program can classify emotional states with an average success rate of 82.31%.https://www.ijimai.org/journal/bibcite/reference/2850emotionbehavioral characteristicsvalencearousalclassification |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Martin Magdin D. Držík J. Reichel S Koprda |
spellingShingle |
Martin Magdin D. Držík J. Reichel S Koprda The Possibilities of Classification of Emotional States Based on User Behavioral Characteristics International Journal of Interactive Multimedia and Artificial Intelligence emotion behavioral characteristics valence arousal classification |
author_facet |
Martin Magdin D. Držík J. Reichel S Koprda |
author_sort |
Martin Magdin |
title |
The Possibilities of Classification of Emotional States Based on User Behavioral Characteristics |
title_short |
The Possibilities of Classification of Emotional States Based on User Behavioral Characteristics |
title_full |
The Possibilities of Classification of Emotional States Based on User Behavioral Characteristics |
title_fullStr |
The Possibilities of Classification of Emotional States Based on User Behavioral Characteristics |
title_full_unstemmed |
The Possibilities of Classification of Emotional States Based on User Behavioral Characteristics |
title_sort |
possibilities of classification of emotional states based on user behavioral characteristics |
publisher |
Universidad Internacional de La Rioja (UNIR) |
series |
International Journal of Interactive Multimedia and Artificial Intelligence |
issn |
1989-1660 1989-1660 |
publishDate |
2021-03-01 |
description |
The classification of user's emotions based on their behavioral characteristic, namely their keyboard typing and mouse usage pattern is an effective and non-invasive way of gathering user's data without imposing any limitations on their ability to perform tasks. To gather data for the classifier we used an application, the Emotnizer, which we had developed for this purpose. The output of the classification is categorized into 4 emotional categories from Russel's complex circular model - happiness, anger, sadness and the state of relaxation. The sample of the reference database consisted of 50 students. Multiple regression analyses gave us a model, that allowed us to predict the valence and arousal of the subject based on the input from the keyboard and mouse. Upon re-testing with another test group of 50 students and processing the data we found out our Emotnizer program can classify emotional states with an average success rate of 82.31%. |
topic |
emotion behavioral characteristics valence arousal classification |
url |
https://www.ijimai.org/journal/bibcite/reference/2850 |
work_keys_str_mv |
AT martinmagdin thepossibilitiesofclassificationofemotionalstatesbasedonuserbehavioralcharacteristics AT ddrzik thepossibilitiesofclassificationofemotionalstatesbasedonuserbehavioralcharacteristics AT jreichel thepossibilitiesofclassificationofemotionalstatesbasedonuserbehavioralcharacteristics AT skoprda thepossibilitiesofclassificationofemotionalstatesbasedonuserbehavioralcharacteristics AT martinmagdin possibilitiesofclassificationofemotionalstatesbasedonuserbehavioralcharacteristics AT ddrzik possibilitiesofclassificationofemotionalstatesbasedonuserbehavioralcharacteristics AT jreichel possibilitiesofclassificationofemotionalstatesbasedonuserbehavioralcharacteristics AT skoprda possibilitiesofclassificationofemotionalstatesbasedonuserbehavioralcharacteristics |
_version_ |
1724232618679992320 |