Smart Grievances Redressal Dashboard

Introduction

Smart_Grievances_Redressal is a dashboard made by Team Scooptroop for monitoring people complaints against posted in various social media handles, like twitter as well as the grievances portal. .

Built With

• Dash - Main server and interactive components
• Plotly Python - Used to create the interactive plots
• Google Translate - Translate marathi/hindi or code mixed language into english
• Amazon transcribe - To convert speech to text, yet to be integrated with frontend
• We have also facilitated the use of amazon cloud 9 along with EC2 instance and lambda function generator to facilitate this feature as an independent API, which is able to handle large and live inputs and produce the output

Unique Features

• Classifies complaints without human intervention according to the department
• Text classification using deep learning approaches such as CNN and LSTM
• Modular use of Twitter API to get the most relevant data
• Code-mixed laguage could also be used - Translator
• Extensive database
• Word embeddings to deal with extra noisy data

ScreenShots

Requirements

We suggest you to create a separate virtual environment running Python 3 for this app, and install all of the required dependencies there. Run in Terminal/Command Prompt:

git clone https://github.com/purplepotion/Smart_Grievances_Redressal
python3 -m virtualenv venv
To run only the model: 
* cd multi-class-text-classification-cnn/
* python data_helpers.py
* python text_CNN.py
* python train.py
* python predict.py

To run the dashboard: Python index.py

In UNIX system:

source venv/bin/activate

In Windows:

venv\Scripts\activate

To install all of the required packages to this environment, simply run:

pip install -r requirements.txt

and all of the required pip packages, will be installed, and the app will be able to run.

How to use this app

Run this app locally by:

python index.py

Open http://0.0.0.0:8050/ in your browser, you will see a live-updating dashboard.

What does this app shows

Key words are displayed according to the department and the frequency graph of the complaints are dispalyed in the analytics dashboard

Resources and references

• Smart complaints dispatching