Skip to content

Tweet sentiment Analysis using deep learning method and model deployment using Flask and Swagger

Notifications You must be signed in to change notification settings

aldimeolaalfarisy/Tweet-Sentiment-Analysis

Repository files navigation

Tweet-Sentiment-Analysis

image

Background

Sentiment is an opinion or view of something. Meanwhile, sentiment analysis itself is the process of analyzing any digital text to determine whether the emotional tone of the message is positive, negative, or neutral, including text on social media (twitter).

The application of sentiment analysis is not limited to social media. Many companies apply sentiment analysis to improve their products or services based on specific customer reviews.

So, we try to analyze the sentiments in the existing tweets and create a system (API) that can classify each tweet sentiment. We use deep learning methods (RNN and LSTM) in this sentiment analysis.

Objectives

  • Identify the distribution of each positive, neutral, and negative tweet sentiments
  • Get the best performing model used to predict sentiment
  • Creating an engine/API that can classify the given sentiments

About

Tweet sentiment Analysis using deep learning method and model deployment using Flask and Swagger

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published