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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 OpenFraming: open-sourced tool for computational framing analysis of multilingual data Sun, Yimeng; Tofu, David Assefa; Halim, Edward Edberg. - : Association for Computational Linguistics, 2021 BASE Show details 2 "Wikily" Supervised Neural Translation Tailored to Cross-Lingual Tasks ... Rasooli, Mohammad Sadegh; Callison-Burch, Chris; Wijaya, Derry Tanti. - : arXiv, 2021 BASE Show details 3 Majority Voting with Bidirectional Pre-translation For Bitext Retrieval ... Jones, Alex; Wijaya, Derry Tanti. - : arXiv, 2021 BASE Show details 4 Resolving pronouns in Twitter streams: context can help! Wijaya, Derry Tanti; Andy, Anietie; Callison-Burch, Chris. - : Association for Computational Linguistics, 2020 BASE Show details 5 Winter is here: summarizing Twitter streams related to pre-scheduled events Andy, Anietie; Wijaya, Derry Tanti; Callison-Burch, Chris. - : Association for Computational Linguistics, 2019 BASE Show details 6 Detecting frames in news headlines and its application to analyzing news framing trends surrounding U.S. gun violence Liu, Siyi; Guo, Lei; Mays, Kate; Betke, Margrit; Wijaya, Derry Tanti. - : Association for Computational Linguistics, 2019 Abstract: Different news articles about the same topic often offer a variety of perspectives: an article written about gun violence might emphasize gun control, while another might promote 2nd Amendment rights, and yet a third might focus on mental health issues. In communication research, these different perspectives are known as “frames”, which, when used in news media will influence the opinion of their readers in multiple ways. In this paper, we present a method for effectively detecting frames in news headlines. Our training and performance evaluation is based on a new dataset of news headlines related to the issue of gun violence in the United States. This Gun Violence Frame Corpus (GVFC) was curated and annotated by journalism and communication experts. Our proposed approach sets a new state-of-the-art performance for multiclass news frame detection, significantly outperforming a recent baseline by 35.9% absolute difference in accuracy. We apply our frame detection approach in a large scale study of 88k news headlines about the coverage of gun violence in the U.S. between 2016 and 2018. ; Published version URL: https://doi.org/10.18653/v1/k19-1047 https://hdl.handle.net/2144/40713 BASE Hide details

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