@inproceedings{d7c4ab3a1b4340cfa12aed2b68e3e6a9,
title = "Measuring Linguistic Synchrony in Psychotherapy",
abstract = "We study the phenomenon of linguistic synchrony between clients and therapists in a psychotherapy process. Linguistic Synchrony (LS) can be viewed as any observed interdependence or association between more than one person{\textquoteright}s linguistic behavior. Accordingly, we establish LS as a methodological task. We suggest a LS function that applies a linguistic similarity measure based on the Jensen-Shannon distance across the observed part-of-speech tag distributions (JSDuPos) of the speakers in different time frames. We perform a study over a unique corpus of 872 transcribed sessions, covering 68 clients and 59 therapists. After establishing the presence of client-therapist LS, we verify its association with therapeutic alliance and treatment outcome (measured using WAI and ORS), and additionally analyse the behavior of JSDuPos throughout treatment. Results indicate that (1) higher linguistic similarity at the session level associates with higher therapeutic alliance as reported by the client and therapist at the end of the session, (2) higher linguistic similarity at the session level associates with higher level of treatment outcome as reported by the client at the beginnings of the next sessions, (3) there is a significant linear increase in linguistic similarity throughout treatment, (4) surprisingly, higher LS associates with lower treatment outcome. Finally, we demonstrate how the LS function can be used to interpret and explore the mechanism for synchrony.1",
author = "Natalie Shapira and Dana Atzil-Slonim and Mashiach, {Rivka Tuval} and Ori Shapira",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 8th Workshop on Computational Linguistics and Clinical Psychology, CLPsych 2022 ; Conference date: 15-07-2022",
year = "2022",
language = "الإنجليزيّة",
series = "CLPsych 2022 - 8th Workshop on Computational Linguistics and Clinical Psychology, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "158--176",
editor = "Ayah Zirikly and Dana Atzil-Slonim and Maria Liakata and Steven Bedrick and Bart Desmet and Molly Ireland and Andrew Lee and Sean MacAvaney and Matthew Purver and Rebecca Resnik and Andrew Yates",
booktitle = "CLPsych 2022 - 8th Workshop on Computational Linguistics and Clinical Psychology, Proceedings",
address = "الولايات المتّحدة",
}