@inproceedings{ali-hassan-2022-survey,
title = "A Survey of Computational Framing Analysis Approaches",
author = "Ali, Mohammad and
Hassan, Naeemul",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.633",
doi = "10.18653/v1/2022.emnlp-main.633",
pages = "9335--9348",
abstract = "Framing analysis is predominantly qualitative and quantitative, examining a small dataset with manual coding. Easy access to digital data in the last two decades prompts scholars in both computation and social sciences to utilize various computational methods to explore frames in large-scale datasets. The growing scholarship, however, lacks a comprehensive understanding and resources of computational framing analysis methods. Aiming to address the gap, this article surveys existing computational framing analysis approaches and puts them together. The research is expected to help scholars and journalists gain a deeper understanding of how frames are being explored computationally, better equip them to analyze frames in large-scale datasets, and, finally, work on advancing methodological approaches.",
}
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%0 Conference Proceedings
%T A Survey of Computational Framing Analysis Approaches
%A Ali, Mohammad
%A Hassan, Naeemul
%Y Goldberg, Yoav
%Y Kozareva, Zornitsa
%Y Zhang, Yue
%S Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates
%F ali-hassan-2022-survey
%X Framing analysis is predominantly qualitative and quantitative, examining a small dataset with manual coding. Easy access to digital data in the last two decades prompts scholars in both computation and social sciences to utilize various computational methods to explore frames in large-scale datasets. The growing scholarship, however, lacks a comprehensive understanding and resources of computational framing analysis methods. Aiming to address the gap, this article surveys existing computational framing analysis approaches and puts them together. The research is expected to help scholars and journalists gain a deeper understanding of how frames are being explored computationally, better equip them to analyze frames in large-scale datasets, and, finally, work on advancing methodological approaches.
%R 10.18653/v1/2022.emnlp-main.633
%U https://aclanthology.org/2022.emnlp-main.633
%U https://doi.org/10.18653/v1/2022.emnlp-main.633
%P 9335-9348
Markdown (Informal)
[A Survey of Computational Framing Analysis Approaches](https://aclanthology.org/2022.emnlp-main.633) (Ali & Hassan, EMNLP 2022)
ACL
- Mohammad Ali and Naeemul Hassan. 2022. A Survey of Computational Framing Analysis Approaches. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 9335–9348, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.