@inproceedings{perez-rosas-etal-2019-makes,
title = "What Makes a Good Counselor? Learning to Distinguish between High-quality and Low-quality Counseling Conversations",
author = "P{\'e}rez-Rosas, Ver{\'o}nica and
Wu, Xinyi and
Resnicow, Kenneth and
Mihalcea, Rada",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-1088",
doi = "10.18653/v1/P19-1088",
pages = "926--935",
abstract = "The quality of a counseling intervention relies highly on the active collaboration between clients and counselors. In this paper, we explore several linguistic aspects of the collaboration process occurring during counseling conversations. Specifically, we address the differences between high-quality and low-quality counseling. Our approach examines participants{'} turn-by-turn interaction, their linguistic alignment, the sentiment expressed by speakers during the conversation, as well as the different topics being discussed. Our results suggest important language differences in low- and high-quality counseling, which we further use to derive linguistic features able to capture the differences between the two groups. These features are then used to build automatic classifiers that can predict counseling quality with accuracies of up to 88{\%}.",
}
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<abstract>The quality of a counseling intervention relies highly on the active collaboration between clients and counselors. In this paper, we explore several linguistic aspects of the collaboration process occurring during counseling conversations. Specifically, we address the differences between high-quality and low-quality counseling. Our approach examines participants’ turn-by-turn interaction, their linguistic alignment, the sentiment expressed by speakers during the conversation, as well as the different topics being discussed. Our results suggest important language differences in low- and high-quality counseling, which we further use to derive linguistic features able to capture the differences between the two groups. These features are then used to build automatic classifiers that can predict counseling quality with accuracies of up to 88%.</abstract>
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%0 Conference Proceedings
%T What Makes a Good Counselor? Learning to Distinguish between High-quality and Low-quality Counseling Conversations
%A Pérez-Rosas, Verónica
%A Wu, Xinyi
%A Resnicow, Kenneth
%A Mihalcea, Rada
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F perez-rosas-etal-2019-makes
%X The quality of a counseling intervention relies highly on the active collaboration between clients and counselors. In this paper, we explore several linguistic aspects of the collaboration process occurring during counseling conversations. Specifically, we address the differences between high-quality and low-quality counseling. Our approach examines participants’ turn-by-turn interaction, their linguistic alignment, the sentiment expressed by speakers during the conversation, as well as the different topics being discussed. Our results suggest important language differences in low- and high-quality counseling, which we further use to derive linguistic features able to capture the differences between the two groups. These features are then used to build automatic classifiers that can predict counseling quality with accuracies of up to 88%.
%R 10.18653/v1/P19-1088
%U https://aclanthology.org/P19-1088
%U https://doi.org/10.18653/v1/P19-1088
%P 926-935
Markdown (Informal)
[What Makes a Good Counselor? Learning to Distinguish between High-quality and Low-quality Counseling Conversations](https://aclanthology.org/P19-1088) (Pérez-Rosas et al., ACL 2019)
ACL