KU-CST at the Profiling Fake News spreaders Shared Task---Notebook for PAN at CLEF 2020
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Documents
- agirrezabal_2020
Final published version, 140 KB, PDF document
In this document we present our approach for profiling fake news spreaders. The model relies on semantic features, part-of-speech tag related features and other simple features. We have reached an accuracy of 0.697 and 0.810 for English and Spanish, respectively, on validation data. Test accuracies using these same models reach 0.690 and 0.725 for English and Spanish data. We believe that this is a simple and robust model that could potentially be used as a baseline for this task.
Original language | English |
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Title of host publication | CLEF 2020 Labs and Workshops, Notebook Papers : CEUR-WS.org |
Number of pages | 5 |
Publisher | CEUR-WS.org |
Publication date | 2020 |
Publication status | Published - 2020 |
Links
- https://pan.webis.de/downloads/publications/papers/agirrezabal_2020.pdf
Final published version
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