Testing and Comparing Computational Approaches for Identifying the Language of Framing in Political News
Published 1 January 2015Open access
Eric P. S. Baumer, Elisha Elovic, Ying Qin, Francesca Polletta, Geri Gay
Citations92
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TL;DR
Results show that the best performing classifiers achieve performance comparable to that of human annotators, and they indicate which aspects of language most pertain to framing.
Abstract
Eric Baumer, Elisha Elovic, Ying Qin, Francesca Polletta, Geri Gay. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2015.
Keywords
Computer ScienceSocial Sciences
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