@inproceedings{alexeeva-etal-2023-annotating,
title = "Annotating and Training for Population Subjective Views",
author = "Alexeeva, Maria and
Hyland, Caroline and
Alcock, Keith and
Cohen, Allegra A. Beal and
Kanyamahanga, Hubert and
Anni, Isaac Kobby and
Surdeanu, Mihai",
editor = "Barnes, Jeremy and
De Clercq, Orph{\'e}e and
Klinger, Roman",
booktitle = "Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, {\&} Social Media Analysis",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.wassa-1.36",
doi = "10.18653/v1/2023.wassa-1.36",
pages = "416--430",
abstract = "In this paper, we present a dataset of subjective views (beliefs and attitudes) held by individuals or groups. We analyze the usefulness of the dataset by training a neural classifier that identifies belief-containing sentences that are relevant for our broader project of interest{---}scientific modeling of complex systems. We also explore and discuss difficulties related to annotation of subjective views and propose ways of addressing them.",
}
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<abstract>In this paper, we present a dataset of subjective views (beliefs and attitudes) held by individuals or groups. We analyze the usefulness of the dataset by training a neural classifier that identifies belief-containing sentences that are relevant for our broader project of interest—scientific modeling of complex systems. We also explore and discuss difficulties related to annotation of subjective views and propose ways of addressing them.</abstract>
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%0 Conference Proceedings
%T Annotating and Training for Population Subjective Views
%A Alexeeva, Maria
%A Hyland, Caroline
%A Alcock, Keith
%A Cohen, Allegra A. Beal
%A Kanyamahanga, Hubert
%A Anni, Isaac Kobby
%A Surdeanu, Mihai
%Y Barnes, Jeremy
%Y De Clercq, Orphée
%Y Klinger, Roman
%S Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F alexeeva-etal-2023-annotating
%X In this paper, we present a dataset of subjective views (beliefs and attitudes) held by individuals or groups. We analyze the usefulness of the dataset by training a neural classifier that identifies belief-containing sentences that are relevant for our broader project of interest—scientific modeling of complex systems. We also explore and discuss difficulties related to annotation of subjective views and propose ways of addressing them.
%R 10.18653/v1/2023.wassa-1.36
%U https://aclanthology.org/2023.wassa-1.36
%U https://doi.org/10.18653/v1/2023.wassa-1.36
%P 416-430
Markdown (Informal)
[Annotating and Training for Population Subjective Views](https://aclanthology.org/2023.wassa-1.36) (Alexeeva et al., WASSA 2023)
ACL
- Maria Alexeeva, Caroline Hyland, Keith Alcock, Allegra A. Beal Cohen, Hubert Kanyamahanga, Isaac Kobby Anni, and Mihai Surdeanu. 2023. Annotating and Training for Population Subjective Views. In Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 416–430, Toronto, Canada. Association for Computational Linguistics.