Identifying emotion by keystroke dynamics and text pattern analysis.
Emotion is a cognitive process and is one of the important characteristics of human beings that makes them different from machines. Traditionally, interactions between humans and machines like computers do not exhibit any emotional exchanges. If we could build any system that is intelligent enough t...
| Publicado en: | Behaviour & Information Technology Vol. 33; no. 9; pp. 987 - 997 |
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| Autores principales: | , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Sep2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103977254&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103977254 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0144929X B6Q jtl: Behaviour & Information Technology issn: 0144929X maglogo: Y pubinfo: dt: Sep2014 vid: 33 iid: 9 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 103977254 97189140 10.1080/0144929X.2014.907343 103977254 ppf: 987 ppct: 10 formats: tig: atl: Identifying emotion by keystroke dynamics and text pattern analysis. aug: au: Nahin, A.F.M. Nazmul Haque Alam, Jawad Mohammad Mahmud, Hasan Hasan, Kamrul affil: Systems and Software Lab (SSL), Department of Computer Science and Engineering (CSE), Islamic University of Technology (IUT), Gazipur1704, Bangladesh sug: subj: Emotions User-Computer Interface Keyboards Human Algorithms Software ab: Emotion is a cognitive process and is one of the important characteristics of human beings that makes them different from machines. Traditionally, interactions between humans and machines like computers do not exhibit any emotional exchanges. If we could build any system that is intelligent enough to interact with humans that involves emotions, that is, it can detect user emotions and change its behaviour accordingly, then using machines could be more effective and friendly. Many approaches have been taken to detect user emotions. Affective computing is the field that detects user emotion in a particular moment. Our approach in this paper is to detect user emotions by analysing the keyboard typing patterns of the user and the type of texts (words, sentences) typed by them. This combined analysis gives us a promising result showing a substantial number of emotional states detected from user input. Several machine learning algorithms were used to analyse keystroke timing attributes and text pattern. We have chosen keystroke because it is the cheapest and most available medium to interact with computers. We have considered seven emotional classes for classifying the emotional states. For text pattern analysis, we have used vector space model with Jaccard similarity method to classify free-text input. Our combined approach showed above 80% accuracies in identifying emotions. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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