Framing Unpacked: A Semi-Supervised Interpretable Multi-View Model of Media Frames
Shima Khanehzar, Trevor Cohn, Gosia Mikolajczak, Andrew Turpin, Lea Frermann
Abstract
Understanding how news media frame political issues is important due to its impact on public attitudes, yet hard to automate. Computational approaches have largely focused on classifying the frame of a full news article while framing signals are often subtle and local. Furthermore, automatic news analysis is a sensitive domain, and existing classifiers lack transparency in their predictions. This paper addresses both issues with a novel semi-supervised model, which jointly learns to embed local information about the events and related actors in a news article through an auto-encoding framework, and to leverage this signal for document-level frame classification. Our experiments show that: our model outperforms previous models of frame prediction; we can further improve performance with unlabeled training data leveraging the semi-supervised nature of our model; and the learnt event and actor embeddings intuitively corroborate the document-level predictions, providing a nuanced and interpretable article frame representation.- Anthology ID:
- 2021.naacl-main.174
- Volume:
- Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- Kristina Toutanova, Anna Rumshisky, Luke Zettlemoyer, Dilek Hakkani-Tur, Iz Beltagy, Steven Bethard, Ryan Cotterell, Tanmoy Chakraborty, Yichao Zhou
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2154–2166
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2021.naacl-main.174/
- DOI:
- 10.18653/v1/2021.naacl-main.174
- Cite (ACL):
- Shima Khanehzar, Trevor Cohn, Gosia Mikolajczak, Andrew Turpin, and Lea Frermann. 2021. Framing Unpacked: A Semi-Supervised Interpretable Multi-View Model of Media Frames. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 2154–2166, Online. Association for Computational Linguistics.
- Cite (Informal):
- Framing Unpacked: A Semi-Supervised Interpretable Multi-View Model of Media Frames (Khanehzar et al., NAACL 2021)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2021.naacl-main.174.pdf
- Code
- shinyemimalef/FRISS