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MeSHx-Notes: Web-System for Clinical Notes Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Analysis of Topic Propagation in Therapy Sessions Using Partially Labeled Latent Dirichlet Allocation

Authors : Ilyas Chaoua, Sergio Consoli, Aki Härmä, Rim Helaoui, Diego Reforgiato Recupero

Published in: Artificial Intelligence in Health

Publisher: Springer International Publishing

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Abstract

The full comprehension of how topics change within psychotherapeutic conversation is key for assessment and therapeutic strategies to adopt by the counselor to the patients. That might enable artificial intelligence (AI) approaches to recommend the most suitable strategy for a new patient. Basically, understanding the topics dynamics of previous cases allows choosing the best therapy to perform for new patients depending on their current conversations.
In this paper we leverage Partially Labeled Dirichlet Allocation with the goal to detect and track topics in real-life psychotherapeutic conversations. On the one hand, the detection of topics allows us identifying the semantic themes of the current therapeutic conversation and predicting topics ad-hoc for each talk-turn between the patient and the counselor. On the other hand, the tracking of topics is key to understand and explore the dynamics of the conversation giving insights and tips on logic and strategy to adopt.
We point out that the entire conversation is structured and modeled according to a sequence of ongoing topics that might propagate through each talk-turn. We present a new method that combines topic modeling and transitions matrices that gives important information to counselors for their therapeutic strategies.

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Footnotes
5
For example, the word Family could correspond to a top level topic, while Family violence and Child abuse would be associated to the second and third levels respectively. Up to 575 subjects have been used in the three levels in total.
 
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Metadata
Title
Analysis of Topic Propagation in Therapy Sessions Using Partially Labeled Latent Dirichlet Allocation
Authors
Ilyas Chaoua
Sergio Consoli
Aki Härmä
Rim Helaoui
Diego Reforgiato Recupero
Copyright Year
2019
Book
Artificial Intelligence in Health

Print ISBN: 978-3-030-12737-4

Electronic ISBN: 978-3-030-12738-1

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-12738-1_5

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