Investigating Mental Wellbeing in the Technology Workplace using Machine Learning Techniques

Tahmid Alam, Tianhua Chen, Magda Bucholc, Grigoris Antoniou

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


With the technology industry becoming steadily more and more populated, professionals within the field are finding themselves prone to suffering from different mental health issues. This is accompanied with more willing to share and discuss the issue as well as more resources put available to support sufferers. Bearing the aim to understand better the mental wellbeing of those working in the technological workplace, this paper utilise machine learning techniques to analyse questionnaire survey data acquired from a non-profit corporation of Open Source Mental Illness (OSMI), whereby unsupervised machine learning was used to identify clusters and potential patterns shared between the OSMI respondents; wile artificial neural network was used to analyse whether it’s possible to establish, based on the survey responses, if an individual suffers from mental health problems.
Original languageEnglish
Title of host publicationArtificial Intelligence in Healthcare
ISBN (Electronic)978-981-19-5272-2
Publication statusPublished online - 26 Oct 2022


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