Sarcasm Detection using Bidirectional Encoder Representations from Transformers and Graph Convolutional Network

This repository contains the code used in our paper:

Sarcasm Detection using Bidirectional Encoder Representations from Transformers and Graph Convolutional Network

International Conference on Machine Learning and Data Mining (ICMLDE), 2022

Anuraj Mohan, Abhilash M Nair, Bhadra Jayakumar, Sanjay Muraleedharan
Department of Computer Science and Engineering, NSS College of Engineering, Palakkad, Kerala, India

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Requirements

• numpy
• spacy
• torch
• scikit-learn
• matplotlib
• pytorch-pretrained-bert

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Usage

• Install the dependencies

pip3 install -r requirements.txt

• Download spaCy language model

python3 -m spacy download en

• Generate adjacency and affective dependency graphs

python3 graph.py

• Train the model. Optional arguments can be found in train.py

python3 train.py

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CREDITS

• The affective knowledge used in this work is from SenticNet.
• The code in this repository partially relies on ADGCN and SenticGCN.

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LICENCE

This repository is licensed under MIT License. See LICENSE for full licensing text.