Gift-Ojeabulu / Customer-Sentiment-Analysis

This sentiment was performed on Twitter to determine overall opinion on US Airlines. Companies and brands often utilize sentiment analysis to monitor brand reputation across social media platforms or across the web as a whole. An application of Data Science/Machine Learning in the Aviation Industry.

Home Page:https://avaition-users-sentiment.herokuapp.com/

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Streamlit App

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This project is one of my machine learning and data-driven web apps made using Streamlit. The goal of this project is to visualize various twitter sentiment and determine overall opinion on US Airlines. An application of Data Science/Machine Learning for problem-solving in the Aviation Industry.

About the Dataset

The dataset was scraped from Twitter in February 2015 and contributors were first asked to classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service"). More details about the dataset can be found here

About

This sentiment was performed on Twitter to determine overall opinion on US Airlines. Companies and brands often utilize sentiment analysis to monitor brand reputation across social media platforms or across the web as a whole. An application of Data Science/Machine Learning in the Aviation Industry.

https://avaition-users-sentiment.herokuapp.com/


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