TY - JOUR
KW - Emotion
KW - Behavioral Characteristics
KW - Valence
KW - Arousal
KW - Classification
AU - Martin Magdin
AU - D. Držík
AU - J. Reichel
AU - S Koprda
AB - 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%.
IS - Regular Issue
M1 - 4
N2 - 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%.
PY - 2020
SP - 97
EP - 104
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - The Possibilities of Classification of Emotional States Based on User Behavioral Characteristics
UR - https://www.ijimai.org/journal/sites/default/files/2020-11/ijimai_6_4_10.pdf
VL - 6
SN - 1989-1660
ER -