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arXiv · 2101.03717

Constraint 2021: Machine Learning Models for COVID-19 Fake News Detection Shared Task

Thomas Felber
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Abstract

In this system paper we present our contribution to the Constraint 2021 COVID-19 Fake News Detection Shared Task, which poses the challenge of classifying COVID-19 related social media posts as either fake or real. In our system, we address this challenge by applying classical machine learning algorithms together with several linguistic features, such as n-grams, readability, emotional tone and punctuation. In terms of pre-processing, we experiment with various steps like stop word removal, stemming/lemmatization, link removal and more. We find our best performing system to be based on a linear SVM, which obtains a weighted average F1 score of 95.19% on test data, which lands a place in the middle of the leaderboard (place 80 of 167).

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Thomas Felber. 2021-01-11. Constraint 2021: Machine Learning Models for COVID-19 Fake News Detection Shared Task. https://arxiv.org/abs/2101.03717

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