Reddit Sentiment Analysis

Inspiration

The inspiration behind Reddit Sentiment Analysis stems from the desire to decipher and understand the complex tapestry of emotions and opinions prevalent in the vast Reddit community. Recognizing the need for a tool that can provide quick insights into sentiment dynamics led to the inception of this project.

What it does

Reddit Sentiment Analysis is a powerful tool that delves into the sentiments expressed in phrases across Reddit. It enables users to explore the emotional pulse of various communities or assess the prevailing mood on specific topics. Whether you're a stock trader looking for quick investment insights or a marketer wanting to evaluate brand sentiment, this tool has you covered.

How we built it

Frontend: Developed with React JS, our user-friendly interface provides a seamless experience for users to input phrases and receive sentiment analysis results.
Backend: Powered by Python Flask, the backend efficiently handles user requests, communicates with the sentiment analysis model, and orchestrates the overall functioning of the application.
Sentiment Analysis Model: We leverage BERT (Bidirectional Encoder Representations from Transformers) for sentiment analysis, classifying phrases into Positive (POS), Neutral (NEU), or Negative (NEG) sentiments. BERT's contextual understanding ensures accurate sentiment predictions.
Topic Modeling: The application also employs LdaModel from gensim for topic modeling, enabling users to explore and understand the prevailing themes within the Reddit community.

Challenges we ran into

The model is difficult to search for prebuilt models that are curated for reddit content.
The models from HuggingFace is not optimal and is slower than our requirements.
Not enough experience in frontend, making the loading bar is challenging because of state management.