Unsupervised aspect based sentiment analysis of JetBlue reviews
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What's better than a brand you can trust? A human you can trust! Our goal is to emphasize the human culture around JetBlue through compilation of web-scraped data and analysis through multiple tools.
Our program collects data from websites about customer's experience with flights and uses natural language processing to determine their sentiment towards the airways they used.
This project uses google cloud's natural language processing to process years worth of tweets and Yelp reviews in order to give an idea of customer sentiment regarding airlines.
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Visualizing and analyzing data of customer's sentiments through social media to hypothesize recommendations for JetBlue
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Social media can be used a great source of customer feedback. We utilize Twitter's data to collect customer feedback on JetBlue company and analyze. It makes it possible to great picture to address it
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