Hate Speech Detection in Tweets

This repository include a solution for HaSpeeDe3 challenge, focuesed on Hate Speech Detection in Twitter data using binary classification models. The tasks include both in-domain detection (within the same dataset) and cross-domain detection (across different datasets). Participants can use textual data alone or combine it with contextual metadata for improved accuracy.

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Tasks Overview

Task A: Political Hate Speech Detection

Goal: Classify whether tweets contain political hate speech.

• Sub-tasks:
  • Textual: Use only the tweet content from the PolicyCorpusXL dataset.
  • Contextual: Use tweet content + additional metadata (e.g., author details, friends, replies, retweets).

Task B: Cross-Domain Hate Speech Detection

Goal: Detect hate speech across different domains.

• Sub-tasks:
  • XPoliticalHate: Test on political hate speech (PolicyCorpusXL).
  • XReligiousHate: Test on religious hate speech using the ReligiousHate dataset.

Participants can optionally incorporate external data sources for Task B.

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Dataset Details

• PolicyCorpusXL: Dataset for political hate speech tasks.
• ReligiousHate: Dataset for religious hate speech detection.

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Performance Results (F1 Score)

Team	Task A (textual/contextual)	Task B (XPoliticalHate)	Task B (XReligiousHate)
our team	0.9192	0.9192	0.6476
BERTicelli	0.8976	0.8976	0.5401
CHILab	0.8516	0.8516	-
extremITA	0.9079	0.9079	0.6525
INGEOTEC	0.8845	0.8845	0.5522
LMU	-	0.9014	0.6461
odang4	0.9128	0.9128	0.5213