@inproceedings{freijedo-aduna-etal-2026-degrees,
title = "Degrees of Subjectivity and Their Repercussions in Conversation. The View from Online Interactions",
author = "Freijedo Aduna, Gonzalo and
Giannakidou, Anastasia and
Mari, Alda",
editor = "Hinrichs, Erhard and
Nivre, Joakim and
Osenova, Petya and
Pustejovsky, James and
Zinn, Claus",
booktitle = "Proceedings of the Workshop on Structured Linguistic Data and Evaluation ({SL}i{DE})",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.slide-1.1/",
doi = "10.63317/53p2a7tyghmi",
pages = "1--13",
abstract = "We present the Annotated Reddit Conversation Corpus (ARCC), an English-language dataset of online discussions annotated for Speech Acts and Functional Dependence Relations, designed to investigate how varying degrees of subjectivity influence conversational dynamics and interaction patterns. At the speech act level, we distinguish factual from opinion statements and further classify opinions along a five-degree scale of subjectivity. Functional Dependence Relations capture how segments relate to preceding ones. Analyses show that opinion-discussion contexts feature frequent inter-subjective opinions eliciting explicit agreement and disagreement, while information-exchange contexts exhibit less subjective opinions with responses like answers or requests for clarification. We further demonstrate that a transformer model can predict the subjectivity scale with promising performance. The corpus and annotation guidelines are made available to support future research on opinion expression and automated dialogue analysis."
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<abstract>We present the Annotated Reddit Conversation Corpus (ARCC), an English-language dataset of online discussions annotated for Speech Acts and Functional Dependence Relations, designed to investigate how varying degrees of subjectivity influence conversational dynamics and interaction patterns. At the speech act level, we distinguish factual from opinion statements and further classify opinions along a five-degree scale of subjectivity. Functional Dependence Relations capture how segments relate to preceding ones. Analyses show that opinion-discussion contexts feature frequent inter-subjective opinions eliciting explicit agreement and disagreement, while information-exchange contexts exhibit less subjective opinions with responses like answers or requests for clarification. We further demonstrate that a transformer model can predict the subjectivity scale with promising performance. The corpus and annotation guidelines are made available to support future research on opinion expression and automated dialogue analysis.</abstract>
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%0 Conference Proceedings
%T Degrees of Subjectivity and Their Repercussions in Conversation. The View from Online Interactions
%A Freijedo Aduna, Gonzalo
%A Giannakidou, Anastasia
%A Mari, Alda
%Y Hinrichs, Erhard
%Y Nivre, Joakim
%Y Osenova, Petya
%Y Pustejovsky, James
%Y Zinn, Claus
%S Proceedings of the Workshop on Structured Linguistic Data and Evaluation (SLiDE)
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma de Mallorca, Spain
%F freijedo-aduna-etal-2026-degrees
%X We present the Annotated Reddit Conversation Corpus (ARCC), an English-language dataset of online discussions annotated for Speech Acts and Functional Dependence Relations, designed to investigate how varying degrees of subjectivity influence conversational dynamics and interaction patterns. At the speech act level, we distinguish factual from opinion statements and further classify opinions along a five-degree scale of subjectivity. Functional Dependence Relations capture how segments relate to preceding ones. Analyses show that opinion-discussion contexts feature frequent inter-subjective opinions eliciting explicit agreement and disagreement, while information-exchange contexts exhibit less subjective opinions with responses like answers or requests for clarification. We further demonstrate that a transformer model can predict the subjectivity scale with promising performance. The corpus and annotation guidelines are made available to support future research on opinion expression and automated dialogue analysis.
%R 10.63317/53p2a7tyghmi
%U https://aclanthology.org/2026.slide-1.1/
%U https://doi.org/10.63317/53p2a7tyghmi
%P 1-13
Markdown (Informal)
[Degrees of Subjectivity and Their Repercussions in Conversation. The View from Online Interactions](https://aclanthology.org/2026.slide-1.1/) (Freijedo Aduna et al., SLiDE 2026)
ACL