Sarcasm_Detection_using_Tensorflow

URL: https://github.com/SanjayKhatwani/Sarcasm_Detection_using_Tensorflow

Description:
A deep learning model designed to detect sarcasm in plain text using TensorFlow.

Dependencies

The project requires the following dependencies:

• Anaconda 4.3.1*
• Python 3.5.x
• TextBlob 0.12.0
• TensorFlow 1.0.1**
• Scikit-learn 0.18.1
• SciPy 0.18.1
• NumPy 1.12.1
• NLTK 3.2.2

Project Files

The repository contains four main Python scripts:

1. create_feature_sets.py – Extracts features from the dataset files and generates featuresets.npy.
2. train_and_test.py – Uses featuresets.npy to train the neural network and saves the trained model inside the /model/ directory.
3. exp_replace.py – Preprocesses the data and is used by create_feature_sets.py.
4. Use_NN.py – Loads the trained model and allows users to make predictions using the neural network.

Datasets

The project includes two dataset files:

• negproc.npy
• posproc.npy

Extracted feature sets are stored in featuresets.npy.
The trained model is stored inside the /model/ directory.

Running the Model

1. Run create_feature_sets.py to extract features from the datasets.
2. Run train_and_test.py to train the model using the extracted features.
3. The trained model will be saved inside /model/ and can be used for predictions.
4. Use Use_NN.py to load the model and make predictions by passing an input sentence to the use_neural_network() function.