Machine learning in emotional intelligence studies: a survey.
Research has proven that having high level of emotional intelligence (EI) can reduce the chance of getting mental illness. EI, and its component, can be improved with training, but currently the process is less flexible and very time-consuming. Machine learning (ML), on the other hand, can analyse h...
| Publicado en: | Behaviour & Information Technology Vol. 41; no. 7; pp. 1485 - 1503 |
|---|---|
| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Jun2022
|
| 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=157176883&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157176883 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0144929X B6Q jtl: Behaviour & Information Technology issn: 0144929X maglogo: Y pubinfo: dt: Jun2022 vid: 41 iid: 7 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 157176883 148351852 157176883 157176883 10.1080/0144929X.2021.1877356 157176883 ppf: 1485 ppct: 18 formats: tig: atl: Machine learning in emotional intelligence studies: a survey. aug: au: Dollmat, Khairi Shazwan Abdullah, Nor Aniza affil: Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia sug: subj: Machine Learning Utilization Emotional Intelligence Education Human Neural Networks (Computer) Support Vector Machine Algorithms Implementation Science Logistic Regression Mental Disorders Prevention and Control Psychology Social Skills Empathy ab: Research has proven that having high level of emotional intelligence (EI) can reduce the chance of getting mental illness. EI, and its component, can be improved with training, but currently the process is less flexible and very time-consuming. Machine learning (ML), on the other hand, can analyse huge amount of data to discover useful trends and patterns in shortest time possible. Despite the benefits, ML usage in EI training is scarce. In this paper, we studied 92 journal articles to discover the trend of the ML utilisation in the study of EI and its components. This survey aims to pave way for future studies that could lead to implementation of ML in EI training, and to rope in researchers in psychology and computer science to find possibilities of having a generic ML algorithm for every EI's components. Our findings show an increasing trend to apply ML on EI components, and Support Vector Machine and Neural Network are the two most popular ML algorithms used in those researches. We also found that social skill and empathy are the least exposed EI components to ML. Finally, we provide recommendations for future research direction of ML in EI domain, and EI in ML. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|