Senti-Surfer : A Bilingual Approach to Sentiment Analysis for Social Media

Senti-Surfer is a research project developed by 4th-semester CS students at Kathmandu University, Dhulikhel, as part of our COMP 207 course. The project aims to create a web extension for sentiment analysis of bilingual social media content to gain useful insights from the data.

Getting Started

Prerequisites

Have Node and Anaconda installed in your computer.

Installation

Clone the project

  git clone https://github.com/suwubham/Senti-Surfer

Go to the project directory and install dependencies

  cd Senti-Surfer
  npm install

Create a .env file and add Google and MongoDB API key. Your env file should look like this:

  YTAPI_KEY = your_api_key
  MONGODB_URI = your_api_key

Instructions to obtain API key 🗝️

Build the project

  npm run build

Go to server directory and install dependencies

  cd server
  pip install requirements.txt

Usage

1. Open extension settings in your web browser and activate developer mode.

2. Click on "Load unpacked" to load the dist folder located in the project directory.

3. Go to server directory and start server

    > uvicorn server:app --reload

Documentation

Project Proposal

Authors

• @Shubham Shakya
• @Saral Sainju
• @Subham Shrestha
• @Nisham Ghimire