angelamarpaung99/racism-detection

Racism Detection built using Long Short-Term Memory (LSTM) on Indonesian texts twitter

Table of Contents

• About the Project
  • Dataset
  • Built With
• Getting Started
  • Prerequisites
  • Installation
• Contributing
• Contact

About The Project

This is Racism Detection System that was built to detect racism on Indonesian tweets text. This project uses Long Short-Term Memory Network (LSTM) using Python programming language.

Dataset

Dataset is collected from Twitter. Dataset contains three columns of data: number, tweets, label. Data collected is 686 tweets, in which each of the tweets is labelled manually. Labelled tweets resulted in 511 tweets for class Non_R (Non Racism) and 175 tweets for class R (Racism). Since this dataset is imbalanced, you can do under-sampling to create balanced dataset.

Built With

• Python

Getting Started

You can get dataset from file "dataset_racism.csv". You can run either the python notebook file "Racism Detection.ipynb" or "Racism Detection.py"

Prerequisites

You can run the python notebook file "Racism Detection.ipynb" locally on Jupyter Notebook or Google Colaboratory. You can run the python script file "Racism Detection.py"

Installation

1. Clone the repo

git clone https://github.com/angelamarpaung99/racism-detection.git

2. Enter your own location path of dataset in Racism Detection.py or Racism Detection.ipynb in this line of code

df = pd.read_csv(<FILE PATH LOCATION>, sep=',') 

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b <add-your-new-branch-name>)
3. Commit your Changes (git commit -m 'commit message')
4. Push to the Branch (git push origin <add-your-branch-name>)
5. Open a Pull Request

Contact

Angela Marpaung - [email protected]

Project Link: https://github.com/angelamarpaung99/racism-detection.git