LSTM-for-Sentiment-Analysis

About the project

In this notebook, I implemented a recurrent neural network (Long short-term memory) using PyTorch that performs sentiment analysis.

Here I used a dataset of Amazon baby products reviews, accompanied by product names and rates. You can find it here

Network Architecture

The architecture for this network is shown below.

The layers are as follows:

1. An embedding layer that converts our word tokens (integers) into embeddings of a specific size.

2. An LSTM layer defined by a hidden_state size and number of layers

3. A fully-connected output layer that maps the LSTM layer outputs to a desired output_size

4. A sigmoid activation layer which turns all outputs into a value 0-1; return only the last sigmoid output as the output of this network.

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It is not possible to push model's state_dict here due to its size. If you need it, feel free to contact me.

Getting Started

Dataset

It's a CSV file consisting of reviews of Amazon baby products. You can download it from Kaggle. It consists of product names, reviews, and ratings associated with each. Bellow, you can see dataframe info:

Data columns (total 3 columns):
name	183213 non-null	object
review	182702 non-null	object
rating	183531 non-null	int64

Head of the data:

name	review	rating
Planetwise Flannel	Wipes These flannel wipes are OK, but in my opinion ...	3
Planetwise Wipe Pouch	it came early and was not disappointed. i love...	5
Annas Dream Full Quilt with 2 Shams	Very soft and comfortable and warmer than it l...	5
Stop Pacifier Sucking without tears with Thumb...	This is a product well worth the purchase. I ...	5
Stop Pacifier Sucking without tears with Thumb...	All of my kids have cried non-stop when I trie...	5

Steps

1. Clone the repo

   git clone https://github.com/salehsargolzaee/LSTM-for-Sentiment-Analysis  

2. Make sure you've installed following packages:

   • PyTorch
   • Pandas
   • NumPy

3. Change directory to repo folder

   cd path/to/repo/folder

4. Download the amazon_baby.csv dataset, and place it in this project's home directory, at the location data/amazon_baby.csv.

5. Run jupyter notebook

   jupyter notebook

6. Open Sentiment_RNN_product_review.ipynb

Contact

Saleh Sargolzaee - LinkedIn - salehsargolzaee@gmail.com

Project Link: https://github.com/salehsargolzaee/LSTM-for-Sentiment-Analysis

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