Offensive Language Detection in Social Media

The SemEval-2020 Task 12 was an AI competition focusing on the detection of offensive language on social media platforms. Our team leveraged the teacher-student paradigm to transfer knowledge from a larger model to a smaller one. We outperformed 81 teams with a 93.19% F1-score using a model three times smaller than the team who ranked first.

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Multilingual NLP will grow

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Combining supervised and unsupervised machine learning methods

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Detecting fake news and cyber-bullying

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Problem

SemEval-2020 Task 12 was an AI competition held in 2020. The goal was to use AI to identify offensive language in social media.

offensive language detection in social media

The leaderboard of the competition is presented in the following table.

Approach

We used only the teacher-student paradigm to transfer knowledge from a large model (Teacher) to a small model (Student).

Result

iSemantics team surpassed 81 teams and scored 93.19% F1-score. We achieved this result using a model 3x smaller than the UHH-LT team, who ranked 1st.

A 3x smaller model means 3x faster decision time and 3x lower running cost when hosting on cloud services.

To learn more about automated data labeling techniques, read the full article here.

Offensive Language Detection in Social Media

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