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The application of sentiment analysis to a psychotherapy session : an exploratory study using four general-purpose lexicons
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Orientador(es)
Resumo(s)
In this study we explore the application of sentiment analysis to a complete and in-person
psychotherapy session. Sentiment analysis is a text mining technique that allows for the analysis,
interpretation, and visualization of textual data. We investigate how we can apply a lexicon-based
approach to analyze clinical session data, using four general-purpose lexicons available within an
open-source statistical programming language environment, R.
We conducted our study by comparing the performance of four general-purpose lexicons
to the performance of n = 52 human raters, using inter-rater reliability (IRR) and intraclass
correlation (ICC) measurements. Our findings suggest there is low to moderate agreement between
human ratings and lexicon generated ratings, depending on the lexicon used. There are some
benefits in applying a lexicon-based sentiment analysis approach to psychotherapy session data,
namely the way it efficiently processes and analyses data and allows for novel visualizations of
psychotherapy data. We recommend further investigation into the application of sentiment analysis
as a technique, focusing on the performance of specific-purpose lexicons. We also recommend
further research into comparing the performance of lexicon-based approaches to text classification
approaches to the analysis of psychotherapy data.
Descrição
Dissertação de Mestrado apresentada no ISPA –
Instituto Universitário para obtenção de grau de Mestre na
especialidade de Psicologia Clínica.
Palavras-chave
Sentiment analysis Lexicon-based approach Therapy session data Dicionário de termos Análise de sentimento Dados clínicos de psicoterapia