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%.
| Original language | English (US) |
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| Title of host publication | ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 926-935 |
| Number of pages | 10 |
| ISBN (Electronic) | 9781950737482 |
| State | Published - 2020 |
| Externally published | Yes |
| Event | 57th Annual Meeting of the Association for Computational Linguistics, ACL 2019 - Florence, Italy Duration: Jul 28 2019 → Aug 2 2019 |
Publication series
| Name | ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference |
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Conference
| Conference | 57th Annual Meeting of the Association for Computational Linguistics, ACL 2019 |
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| Country/Territory | Italy |
| City | Florence |
| Period | 7/28/19 → 8/2/19 |
Bibliographical note
Publisher Copyright:© 2019 Association for Computational Linguistics