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SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles

<p>This dataset contains the files and annotations for <a href="https://propaganda.qcri.org/semeval2020-task11/index.html">SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles</a>. The task was composed by two subtasks: span identification (SI) and technique classification (TC). This dataset includes the following:</p> <ul> <li>The text files for training, development, and testing sets for both the SI and the TC tasks.</li> <li>The gold-standard files for the training sets, for both the SI and the TC task</li> </ul> <p>Our propaganda identification initiative remains active. We keep a <a href="https://propaganda.qcri.org/ptc/leaderboard.php">live leader-board</a> reporting the performance of models submited up to date.</p> <p><strong>Reference</strong></p> <p>Giovanni Da San Martino, Alberto Barr&oacute;n-Cede&ntilde;o, Henning Wachsmuth, Rostislav Petrov, and Preslav Nakov. 2020. <a href="https://propaganda.qcri.org/">Task 11: Detection of Propaganda Techniques in News Articles</a>. In Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020). Barcelona, Spain (2020)</p> <p>&nbsp;</p> <pre><code>@InProceedings{SemEval20-11-DaSanMartino, author = "Da San Martino, Giovanni and Barr\'{o}n-Cede\~no, Alberto and Wachsmuth, Henning and Petrov, Rostislav and Nakov, Preslav", title = "{SemEval}-2020 Task 11: {D}etection of Propaganda Techniques in News Articles", pages = "", abstract = "We describe the outcome of the SemEval 2020 Task 11 on the detection of propaganda in news articles. We present two tasks. In the first task, systems are asked to identify specific text spans in a free text where propaganda is being applied. In the second task, systems are asked to identify the propaganda technique being applied in a text span. We describe the construction of the evaluation framework (dataset and evaluation metrics) as well as the approaches explored by the different participants. ", crossref = "SemEval20" }</code></pre> <p>&nbsp;</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
8
Access
16
Reuse readiness
0
Engagement
4

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