OpenFraming: open-sourced tool for computational framing analysis of multilingual data
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Published version
Date
2021
Authors
Bhatia, Vibhu
Akavoor, Vidya
Paik, Sejin
Guo, Lei
Jalal, Mona
Smith, Alyssa
Tofu, David Assefa
Halim, Edward Edberg
Sun, Yimeng
Betke, Margrit
Version
Published version
OA Version
Citation
V. Bhatia, V.P. Akavoor, S. Paik, L. Guo, M. Jalal, A. Smith, D.A. Tofu, E.E. Halim, Y. Sun, M. Betke, P. Ishwar, D.T. Wijaya. 2021. "OpenFraming: Open-sourced Tool for Computational Framing Analysis of Multilingual Data." Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. 2021-11 - 2021-11. https://doi.org/10.18653/v1/2021.emnlp-demo.28
Abstract
When journalists cover a news story, they can cover the story from multiple angles or perspectives. These perspectives are called “frames,” and usage of one frame or another may influence public perception and opinion of the issue at hand. We develop a web-based system for analyzing frames in multilingual text documents. We propose and guide users through a five-step end-to-end computational framing analysis framework grounded in media framing theory in communication research. Users can use the framework to analyze multilingual text data, starting from the exploration of frames in user’s corpora and through review of previous framing literature (step 1-3) to frame classification (step 4) and prediction (step 5). The framework combines unsupervised and supervised machine learning and leverages a state-of-the-art (SoTA) multilingual language model, which can significantly enhance frame prediction performance while requiring a considerably small sample of manual annotations. Through the interactive website, anyone can perform the proposed computational framing analysis, making advanced computational analysis available to researchers without a programming background and bridging the digital divide within the communication research discipline in particular and the academic community in general. The system is available online at http://www.openframing.org, via an API http://www.openframing.org:5000/docs/, or through our GitHub page https://github.com/vibss2397/openFraming.
Description
License
Copyright: ©2021 Association for Computational Linguistics. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited