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Issue Framing in Online Discussion Fora. / Hartmann, Mareike; Jansen, Tallulah; Augenstein, Isabelle; Søgaard, Anders.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, 2019. p. 1401-1407.
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Hartmann, M, Jansen, T
, Augenstein, I & Søgaard, A 2019,
Issue Framing in Online Discussion Fora. in
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, pp. 1401-1407, 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - NAACL-HLT 2019, Minneapolis, United States,
03/06/2019.
https://doi.org/10.18653/v1/N19-1142APA
Hartmann, M., Jansen, T.
, Augenstein, I., & Søgaard, A. (2019).
Issue Framing in Online Discussion Fora. In
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) (pp. 1401-1407). Association for Computational Linguistics.
https://doi.org/10.18653/v1/N19-1142Vancouver
Hartmann M, Jansen T
, Augenstein I, Søgaard A.
Issue Framing in Online Discussion Fora. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics. 2019. p. 1401-1407
https://doi.org/10.18653/v1/N19-1142Author
Hartmann, Mareike ; Jansen, Tallulah ; Augenstein, Isabelle ; Søgaard, Anders. / Issue Framing in Online Discussion Fora. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, 2019. pp. 1401-1407
Bibtex
@inproceedings{48b1d3febc9547e98fb1ffab6bb4c043,
title = "Issue Framing in Online Discussion Fora",
abstract = "In online discussion fora, speakers often make arguments for or against something, say birth control, by highlighting certain aspects of the topic. In social science, this is referred to as issue framing. In this paper, we introduce a new issue frame annotated corpus of online discussions. We explore to what extent models trained to detect issue frames in newswire and social media can be transferred to the domain of discussion fora, using a combination of multi-task and adversarial training, assuming only unlabeled training data in the target domain.",
author = "Mareike Hartmann and Tallulah Jansen and Isabelle Augenstein and Anders S{\o}gaard",
year = "2019",
doi = "10.18653/v1/N19-1142",
language = "English",
pages = "1401--1407",
booktitle = "Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
publisher = "Association for Computational Linguistics",
note = "2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - NAACL-HLT 2019 ; Conference date: 03-06-2019 Through 07-06-2019",
}
RIS
TY - GEN
T1 - Issue Framing in Online Discussion Fora
AU - Hartmann, Mareike
AU - Jansen, Tallulah
AU - Augenstein, Isabelle
AU - Søgaard, Anders
PY - 2019
Y1 - 2019
N2 - In online discussion fora, speakers often make arguments for or against something, say birth control, by highlighting certain aspects of the topic. In social science, this is referred to as issue framing. In this paper, we introduce a new issue frame annotated corpus of online discussions. We explore to what extent models trained to detect issue frames in newswire and social media can be transferred to the domain of discussion fora, using a combination of multi-task and adversarial training, assuming only unlabeled training data in the target domain.
AB - In online discussion fora, speakers often make arguments for or against something, say birth control, by highlighting certain aspects of the topic. In social science, this is referred to as issue framing. In this paper, we introduce a new issue frame annotated corpus of online discussions. We explore to what extent models trained to detect issue frames in newswire and social media can be transferred to the domain of discussion fora, using a combination of multi-task and adversarial training, assuming only unlabeled training data in the target domain.
U2 - 10.18653/v1/N19-1142
DO - 10.18653/v1/N19-1142
M3 - Article in proceedings
SP - 1401
EP - 1407
BT - Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
PB - Association for Computational Linguistics
T2 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - NAACL-HLT 2019
Y2 - 3 June 2019 through 7 June 2019
ER -
