task_categories:
- text-classification
language:
- en
tags:
- health
- tweet
- hate speech
- mental health
- hate speech detection
- hate speech classification
- social media
- mobile health
size_categories:
- 1K<n<10K
Dataset Card for Dataset Name
The dataset is designed to analyze and address hate speech within online platforms. It consists of two sets: the training and testing sets. The two datasets have been labeled and categorized instances of hate speech into nine distinct categories.
Dataset Description
The dataset comprises three key features: tweets, labels (with hate speech denoted as 1 and non-hate speech as 0), and categories (behavior, class, disability, ethnicity, gender, physical appearance, race, religion, sexual orientation).
- Training set: contains a total of 5679 tweets (Hate Speech: 1516 / Non Hate Speech: 4163), and the number of hate speech in each category is not equally distributed.
- Testing set: contains a total of 1000 tweets (Hate Speech: 500 / Non Hate Speech: 500), and the number of hate speech in each category is generally even.
Uses
This dataset can be utilized for various purposes, including but not limited to:
- Developing and training machine learning models for hate speech detection.
- Analyzing the prevalence and patterns of hate speech across different categories.
- Understanding the challenges associated with categorizing hate speech on social media platforms.
Check it out for the example project!
Source Data
The dataset utilized in this study is sourced from Kaggle and named the Hate Speech and Offensive Language dataset. Hate speech instances are identified by selecting tweets within the "class" column.
Annotations
Category labels were generated through an OpenAI API call employing the GPT-3.5 model. It's important to note the instability in category predictions when utilizing GPT-3.5 for label generation, as it tends to predict different categories each time. However, we have confirmed that these tweets were labeled correctly. If there are any misclassified labels, please feel free to reach out. Thank you in advance for your assistance.
Dataset Card Contact
Please feel free to contact me via wh476@cornell.edu!