Social Media Analysis

Try it out: https://olympic-sentiment-analysis-gdgyrsntw-thenaivekid.vercel.app/

Demo Video https://youtu.be/5lwiuEWD7ko

Documentation

Working with data

An easy to use app to visualize what people are talking on social media during an Oympics.

For the sake of demonstration of the app, instead of getting live posts from the social media APIs, we used data of tokyo olympics 2020 that is found here

The EDA can be found in the tokyo_olympics0.ipynb file. The sentiments were predicted using hugging face pretrained model.

from transformers import pipeline

sent_pipeline = pipeline("sentiment-analysis", 
    model='finiteautomata/bertweet-base-sentiment-analysis'
    )   

This model gives {sentiment, sentiment_score} for the input text. EG.

('NEG', 0.7984506487846375)

Precomputed sentiment and score columns are added to dataset for fast accessing and scalability. Now the data and the sentiments are ready to be consumed by the web app.

Web app

Backend

We have used Fast API for making our web app faster. We have three API endpoints:

• /overall: It takes get request and returns title, total number of posts and a list with number of posts with negative, neutral and positive sentiments respectively.
• /sentiments: It takes keyword and filters all the rows with the given keyword . It also returns title, total number of posts and a list with number of posts with negative, neutral and positive sentiments respectively.
• /tweets: It takes keyword, number of posts and sentiment of the posts and returns the filtered posts.

Frontend

We have written frontend on react js and used chart js for visualization. In the src/components we have:

• BarGraph
• PieChart
• Plots: It puts the charts together.
• Sent: It creates a card for an individual keyword query
• Sents: It contains all the Sent items
• Tweets: It shows the actual posts from the social media
• Search: It has a input field to take the keyword and a submit button to call the API for the keyword.

AppRemake.jsx renders all the components in the right order and calls the APIs.

Usage

1. clone the repo
2. To run the backed

cd backend
pip3 install -r requirements.txt
uvicorn main:app --reload

1. To run the frontend

npm install react
cd frontend
npm run dev

live

backend: https://social-media-ashok.onrender.com/greet/
frontend: https://olympic-sentiment-analysis-gdgyrsntw-thenaivekid.vercel.app/