Findings of the NLP4IF-2019 Shared Task on Fine-Grained Propaganda Detection
| Autor: | Giovanni Da San Martino, Alberto Barrón-Cedeño, Preslav Nakov |
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| Přispěvatelé: | Da San Martino, Giovanni, Barrón-Cedeño, Alberto, Nakov, Preslav |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Propaganda techniques Computer Science - Computation and Language business.industry Computer science 68T50 I.2.7 Computer Science - Social and Information Networks computer.software_genre Task (project management) Identification (information) Binary classification Margin (machine learning) Artificial intelligence business computer Computation and Language (cs.CL) Natural language processing propaganda identification shared task |
| Popis: | We present the shared task on Fine-Grained Propaganda Detection, which was organized as part of the NLP4IF workshop at EMNLP-IJCNLP 2019. There were two subtasks. FLC is a fragment-level task that asks for the identification of propagandist text fragments in a news article and also for the prediction of the specific propaganda technique used in each such fragment (18-way classification task). SLC is a sentence-level binary classification task asking to detect the sentences that contain propaganda. A total of 12 teams submitted systems for the FLC task, 25 teams did so for the SLC task, and 14 teams eventually submitted a system description paper. For both subtasks, most systems managed to beat the baseline by a sizable margin. The leaderboard and the data from the competition are available at http://propaganda.qcri.org/nlp4if-shared-task/. propaganda, disinformation, fake news. arXiv admin note: text overlap with arXiv:1910.02517 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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