@inproceedings{frenzel-hautli-janisz-2025-identifying,
title = "Identifying Small Talk in Natural Conversations",
author = "Frenzel, Steffen and
Hautli-Janisz, Annette",
editor = "Kazantseva, Anna and
Szpakowicz, Stan and
Degaetano-Ortlieb, Stefania and
Bizzoni, Yuri and
Pagel, Janis",
booktitle = "Proceedings of the 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2025)",
month = may,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.latechclfl-1.24/",
doi = "10.18653/v1/2025.latechclfl-1.24",
pages = "272--277",
ISBN = "979-8-89176-241-1",
abstract = "Small talk is part and parcel of human interaction and is rather employed to communicate values and opinions than pure information. Despite small talk being an omnipresent phenomenon in spoken language, it is difficult to identify: Small talk is situated, i.e., for interpreting a string of words or discourse units, outside references such as the context of the interlocutors and their previous experiences have to be interpreted.In this paper, we present a dataset of natural conversation annotated with a theoretically well-motivated distillation of what constitutes small talk. This dataset comprises of verbatim transcribed public service encounters in German authorities and are the basis for empirical work in administrative policy on how the satisfaction of the citizen manifests itself in the communication with the authorities. We show that statistical models achieve comparable results to those of state-of-the-art LLMs."
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<abstract>Small talk is part and parcel of human interaction and is rather employed to communicate values and opinions than pure information. Despite small talk being an omnipresent phenomenon in spoken language, it is difficult to identify: Small talk is situated, i.e., for interpreting a string of words or discourse units, outside references such as the context of the interlocutors and their previous experiences have to be interpreted.In this paper, we present a dataset of natural conversation annotated with a theoretically well-motivated distillation of what constitutes small talk. This dataset comprises of verbatim transcribed public service encounters in German authorities and are the basis for empirical work in administrative policy on how the satisfaction of the citizen manifests itself in the communication with the authorities. We show that statistical models achieve comparable results to those of state-of-the-art LLMs.</abstract>
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%0 Conference Proceedings
%T Identifying Small Talk in Natural Conversations
%A Frenzel, Steffen
%A Hautli-Janisz, Annette
%Y Kazantseva, Anna
%Y Szpakowicz, Stan
%Y Degaetano-Ortlieb, Stefania
%Y Bizzoni, Yuri
%Y Pagel, Janis
%S Proceedings of the 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2025)
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-241-1
%F frenzel-hautli-janisz-2025-identifying
%X Small talk is part and parcel of human interaction and is rather employed to communicate values and opinions than pure information. Despite small talk being an omnipresent phenomenon in spoken language, it is difficult to identify: Small talk is situated, i.e., for interpreting a string of words or discourse units, outside references such as the context of the interlocutors and their previous experiences have to be interpreted.In this paper, we present a dataset of natural conversation annotated with a theoretically well-motivated distillation of what constitutes small talk. This dataset comprises of verbatim transcribed public service encounters in German authorities and are the basis for empirical work in administrative policy on how the satisfaction of the citizen manifests itself in the communication with the authorities. We show that statistical models achieve comparable results to those of state-of-the-art LLMs.
%R 10.18653/v1/2025.latechclfl-1.24
%U https://aclanthology.org/2025.latechclfl-1.24/
%U https://doi.org/10.18653/v1/2025.latechclfl-1.24
%P 272-277
Markdown (Informal)
[Identifying Small Talk in Natural Conversations](https://aclanthology.org/2025.latechclfl-1.24/) (Frenzel & Hautli-Janisz, LaTeCHCLfL 2025)
ACL
- Steffen Frenzel and Annette Hautli-Janisz. 2025. Identifying Small Talk in Natural Conversations. In Proceedings of the 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2025), pages 272–277, Albuquerque, New Mexico. Association for Computational Linguistics.