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πŸ’¬A Gated Recurrent Neural Network for Supervised Text Classification: detecting hate speech from different online textual genres.

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BiBiNET: BiLSTM for bipolarity sentiment analysis.

A Gated Recurrent Neural Network for Supervised Text Classification: detecting hate speech from different online textual genres.

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Description

This project was developed for the ”Human Language Technologies” course of Professor Giuseppe Attardi.

Directory structure (main elements)

BiBiNET
  │── src
  β”‚    │── data_import.py                   # process 1/6
  β”‚    │── data_prep.py                     # process 2/6                     
  β”‚    │── preproc.py                       # process 3/6
  β”‚    │── transform.py                     # process 4/6
  β”‚    │── classifiers.py                   # process 5/6
  β”‚    │── test.py                          # process 6/6
  β”‚    │── utilities.py
  β”‚    └── main.py                          # file to run
  └── data
  β”‚    └── forum_data
  β”‚    β”‚   │── all_files.csv                # text
  β”‚    β”‚   └── annotations_metadata.csv     # labels
  β”‚    └── twitter_1
  β”‚    β”‚   └── twitter_dataset.csv       
  β”‚    └── twitter_2
  β”‚    β”‚    │── train.csv                
  β”‚    β”‚    └── test.csv     
  β”‚    └── wikipedia_data
  β”‚         │── train.csv                
  β”‚         └── test.csv    
  └── glove
  β”‚   │── glove.twitter.27B.100d      
  β”‚   └── glove.twitter.27B.200d        
  └── model          
  β”‚   └── model.h5                          # final model   
  └── requirements.txt
  └── report.pdf                            # project guide
  └── README.md
  └── LICENSE  

Quick start

Install Python:
sudo apt install python3

Install pip:
sudo apt install --upgrade python3-pip

Install requirements:
python -m pip install --requirement requirements.txt

Execute main

cd src/
python main.py

Corresponding author

Dr. Diletta Goglia ORCID logo
Postgraduate Student in MSc in Artificial Intelligence
Computer Science department, University of Pisa, Italy
d.goglia@studenti.unipi.it
dilettagoglia.netlify.app

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