Update README.md

Dataset v1:
The dataset is composed of 200,000 tweets. Half of them is Turkish and other half is English. We also have domain information of the hate speech. These domains are Religion, Gender, Race, Politics, Sports. Each domain has 20,000 tweets in each respective language. 5 hate annotations of the tweet are also given. Since we followed Twitter's Terms and Conditions, publish tweet IDs not the tweet content directly. Explanations of the columns of the file are as follows:

Column Name Description
TweetID Twitter ID of the tweet
LangID Language of the tweet 0-Turkish, 1-English
TopicID Domain of the topic 0-Religion, 1-Gender, 2-Race, 3-Politics, 4-Sports
Label_1 Annotation of the first annotator 0-Normal, 1-Offensive, 2-Hate
Label_2 Annotation of the second annotator 0-Normal, 1-Offensive, 2-Hate
Label_3 Annotation of the third annotator 0-Normal, 1-Offensive, 2-Hate
Label_4 Annotation of the fourth annotator 0-Normal, 1-Offensive, 2-Hate
Label_5 Annotation of the fifth annotator 0-Normal, 1-Offensive, 2-Hate
HateLabel Final hate label decision 0-Normal, 1-Offensive, 2-Hate

Dataset v2:
We acknowledge that some annotations in the original dataset (v1) are controversial. Therefore, we publish a more reliable dataset version (v2) that includes only the tweets with more than 80% annotator agreement. The dataset v2 has 128,907 tweets. 60,310 of them are Turkish, and 68,597 are English. Explanations of the columns of the file are as follows:
Column Name Description
TweetID Twitter ID of the tweet
LangID Language of the tweet 0-Turkish, 1-English
TopicID Domain of the topic 0-Religion, 1-Gender, 2-Race, 3-Politics, 4-Sports
HateLabel Final hate label decision 0-Normal, 1-Offensive, 2-Hate

Citation
If you make use of this dataset, please cite following paper.

@InProceedings{toraman2022large,
author = {Toraman, Cagri and \c{S}ahinu\c{c}, Furkan and Yilmaz, Eyup Halit},
title = {Large-Scale Hate Speech Detection with Cross-Domain Transfer},
booktitle = {Proceedings of the Language Resources and Evaluation Conference},
month = {June},
year = {2022},
address = {Marseille, France},
publisher = {European Language Resources Association},
pages = {2215--2225},
url = {https://aclanthology.org/2022.lrec-1.238}
}

README.md

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 license: cc
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+This repository contains the utilized dataset in the LREC 2022 paper "Large-Scale Hate Speech Detection with Cross-Domain Transfer". This study mainly focuses hate speech detection in Turkish and English. In addition, domain transfer success between hate domains is also examined.
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+There are two dataset versions.
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+Dataset v1: The original dataset that includes 100,000 tweets per English and Turkish, published in LREC 2022. The annotations with more than 60% agreement are included.
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+Dataset v2: A more reliable dataset version that includes 68,597 tweets for English and 60,310 for Turkish. The annotations with more than 80% agreement are included.
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