A Review of LIWC and Machine Learning Approaches On Mental Health Diagnosis

Yıl 2023, Cilt: 1 Sayı: 2, 71 - 92, 25.10.2023

Bahar Sert , Selami Varol Ülker

Öz

Machine learning methods are becoming increasingly popular data analysis and enable learning from data in many different fields. In the field of mental healthcare, these methods provide support to mental health professionals in various ways. The diagnosis of mental disorders is one of these areas where machine learning methods can be of assistance. Firstly, Pennebaker and his colleagues developed a computer program for dictionary-based automatic quantitative text analysis which detects many mental disorder diagnosis and symptoms such as depression, schizophrenia and suicidal tendencies through text analysis. In this study, Machine learning and Linguistic Inquiry Word Count (LIWC) studies conducted in the field of mental disorder diagnosis were examined. Researchers aim to integrate LIWC with machine learning to conduct more comprehensive studies. The objective of this study is to examine how combining Machine learning and LIWC methods can detect mental disorder with a focus on comparative research. For this purpose, publications related to machine learning and LIWC in Google Scholar, Web of Science, Scopus, EBSCO, PubMed were examined. Studies utilizing machine learning and LIWC methods in mental health diagnosis were reviewed to establish an overview of the general state of the literature. A comprehensive table summarizing 15 articles examining the impact of integrating machine learning and LIWC on mental disorder identification was compiled. Subsequently, the working principles of machine learning and LIWC were examined and research conducted in the field of mental disorder diagnosis was reviewed. Furthermore, some studies about mental disorder diagnosis were set out in table. Further research particularly those integrating or comparing these two methods needed to better understand machine learning and Linguistic Inquiry Word Count in mental disorder detection.

Anahtar Kelimeler

LIWC, Machine Learning, Mental Disorders, Psychology, Text analysis

Kaynakça

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