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An emotional journey : detecting emotion trajectories in Dutch customer service dialogues

Sofie Labat (UGent) , Amir Hadifar, Thomas Demeester (UGent) and Veronique Hoste (UGent)
(2022) Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022). In COLING 29(4). p.106-112
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Abstract
The ability to track fine-grained emotions in customer service dialogues has many real-world applications, but has not been studied extensively. This paper measures the potential of prediction models on that task, based on a real-world dataset of Dutch Twitter conversations in the domain of customer service. We find that modeling emotion trajectories has a small, but measurable benefit compared to predictions based on isolated turns. The models used in our study are shown to generalize well to different companies and economic sectors.
Keywords
emotion detection, conversational AI, customer service, Dutch

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Citation

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MLA
Labat, Sofie, et al. “An Emotional Journey : Detecting Emotion Trajectories in Dutch Customer Service Dialogues.” Proceedings of the Eighth Workshop on Noisy User-Generated Text (W-NUT 2022), vol. 29, no. 4, Association for Computational Linguistics (ACL), 2022, pp. 106–12.
APA
Labat, S., Hadifar, A., Demeester, T., & Hoste, V. (2022). An emotional journey : detecting emotion trajectories in Dutch customer service dialogues. Proceedings of the Eighth Workshop on Noisy User-Generated Text (W-NUT 2022), 29(4), 106–112. Gyeongju, Republic of Korea: Association for Computational Linguistics (ACL).
Chicago author-date
Labat, Sofie, Amir Hadifar, Thomas Demeester, and Veronique Hoste. 2022. “An Emotional Journey : Detecting Emotion Trajectories in Dutch Customer Service Dialogues.” In Proceedings of the Eighth Workshop on Noisy User-Generated Text (W-NUT 2022), 29:106–12. Gyeongju, Republic of Korea: Association for Computational Linguistics (ACL).
Chicago author-date (all authors)
Labat, Sofie, Amir Hadifar, Thomas Demeester, and Veronique Hoste. 2022. “An Emotional Journey : Detecting Emotion Trajectories in Dutch Customer Service Dialogues.” In Proceedings of the Eighth Workshop on Noisy User-Generated Text (W-NUT 2022), 29:106–112. Gyeongju, Republic of Korea: Association for Computational Linguistics (ACL).
Vancouver
1.
Labat S, Hadifar A, Demeester T, Hoste V. An emotional journey : detecting emotion trajectories in Dutch customer service dialogues. In: Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022). Gyeongju, Republic of Korea: Association for Computational Linguistics (ACL); 2022. p. 106–12.
IEEE
[1]
S. Labat, A. Hadifar, T. Demeester, and V. Hoste, “An emotional journey : detecting emotion trajectories in Dutch customer service dialogues,” in Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022), Gyeongju, Republic of Korea, 2022, vol. 29, no. 4, pp. 106–112.
@inproceedings{8769949,
  abstract     = {{The ability to track fine-grained emotions in customer service dialogues has many real-world applications, but has not been studied extensively. This paper measures the potential of prediction models on that task, based on a real-world dataset of Dutch Twitter conversations in the domain of customer service. We find that modeling emotion trajectories has a small, but measurable benefit compared to predictions based on isolated turns. The models used in our study are shown to generalize well to different companies and economic sectors.}},
  author       = {{Labat, Sofie and Hadifar, Amir and Demeester, Thomas and Hoste, Veronique}},
  booktitle    = {{Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022)}},
  issn         = {{2951-2093}},
  keywords     = {{emotion detection,conversational AI,customer service,Dutch}},
  language     = {{eng}},
  location     = {{Gyeongju, Republic of Korea}},
  number       = {{4}},
  pages        = {{106--112}},
  publisher    = {{Association for Computational Linguistics (ACL)}},
  title        = {{An emotional journey : detecting emotion trajectories in Dutch customer service dialogues}},
  url          = {{https://aclanthology.org/2022.wnut-1.12.pdf}},
  volume       = {{29}},
  year         = {{2022}},
}