Emotion Detection using BiLSTM on Social Media

Dataset

Download dataset (text.csv) from : Emotions

Python Version and Third-Party Libraries

Python Version:

Python Version: 3.10.12

Third-Party Libraries:

1. Pandas: 2.2.2
2. NumPy: 1.26.4
3. Seaborn: 0.13.2
4. Matplotlib: 3.8.0
5. TensorFlow: 2.17.1
6. NLTK (Natural Language Toolkit): 3.9.1
7. scikit-learn: 1.6.0
8. SpaCy: 3.7.5
9. Gensim: 4.3.3

Running the Code

Follow the steps below to run the code in the correct order:

1. Install Python and Third-Party Libraries

Before running the code, ensure that Python 3.10.12 is installed. If necessary, update to this version.

Install the required libraries by running the following command in your terminal:

pip install pandas==2.2.2 numpy==1.26.4 seaborn==0.13.2 matplotlib==3.8.0 tensorflow==2.17.1 nltk==3.9.1 scikit-learn==1.6.0 spacy==3.7.5 gensim==4.3.3

2. Pre_Processing.ipynb

• In the Data Load section:
  Add the path to the dataset file (text.csv).

• In the Export Dataset section:
  Specify the path where the preprocessed dataset will be stored (e.g., preprocessed_dataset.csv).

• Run the file Pre_Processing.ipynb.

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3. Feature_Analysis.ipynb

• In the Data Load section:
  Add the path to the preprocessed dataset (preprocessed_dataset.csv).

• Run the file Feature_Analysis.ipynb.

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4. BiLSTM_Model.ipynb

• In the Data Load section:
  Add the path to the preprocessed dataset (preprocessed_dataset.csv).

• Run the file BiLSTM_Model.ipynb.

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After following the above steps, the code should run successfully and the output should be displayed seamlessly.