What Are People Saying About Airline Companies On Twitter?

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I used natural language processing (NLP) to extract a list of topics from tweets about airlines. I used the Twitter API to collect over 60,000 tweets about four major airlines over the course of two weeks. I discovered conversations about ten topics ranging from customer service, to having fun and traveling, to racism.

The tweets were stored in MongoDB.

I wrote my own cleaning module to handle twitter specific issues such as slang, emojis, twitter handles, and misspellings.
I used spaCy to tokenize and build my corpus.
I used Latent Semantic Analysis (LSA) and KMeans clustering to generate my list of topics.

There are six notebooks in my repository:

1. Getting tweets
2. Cleaning and sentiment analysis
3. More cleaning
4. Lemmatizing
5. Topic Modeling using Latent Semantic Analysis
6. Final Model using LSA and KMeans clustering

Here is a link to an interactive app that I made to summarize my project Airline Tweets
Here is a link to my blog post about the project. Blog Post