Customer Sentiment Analyzer

✈️ Description

Data collected from public domains and social media to achieve an average customer sentiment score displayed in a graph.
Uses dates, sentiment score and magnitude as data.

Requirements

python3
matplotlib - Installation
QtPy5 - Installation

Installing

git clone https://github.com/dannyhollman/yhack2019.git

Usage

Run the main file for GUI

python3 customer_sentiment_analyzer.py

Data

• twitter - tweets related to jetBlue from 2019 to 2013
• yelp - jetBlue, American, Delta and Spirit reviews collected

date, sentiment

Example

File Structure

0. customer_sentiment_analyzer.py - Main function

• def graph_jetblue(): - graph for jetblue analytics.
• def graph_american(): - graph for american analytics.
• def graph_spirit(): - graph for spirit analytics.
• def graph_delta(): - graph for delta analytics.

1. american_yelp_sent.json - list of key, values for american.

2. delta_yelp_sent.json - list of key, values for delta.

3. more_twitter_data.json - list of key, values for jetblue.

4. spirit_yelp_sent.json - list of key, values for spirit.

5. dev - developer files.

• adaptive.json
• american_yelp.json
• delta_yelp.json
• jetblue.json
• jetblue_tripadvisor_sent.json
• jetblue_twitter_sent.json
• jetblue_yelp.json
• jetblue_yelp_sent.json
• main.py
• parse_json_data.py
• sentiment.py
• spirit_yelp.json
• trip_adv_data.py
• trip_advisor_to_file.py
• yelp_data.py
• yelp_reviews.csv
• yelp_scrape_to_csv.py

Story

This project was our entry into the 2019 Yale Hackathon. The challenge we chose was "Crawl Any/All public domain/social media data to get customer’s sentiments of JetBlue." To accomplish this we collected data from various social media and review sites, ran the data through Google's sentiment analyzer, and graphed the output.

Authors

• Danny Hollman Github LinkedIn Twitter
• William Dyrland-Marquis
• Jose Alvarez de Lugo
• Stephen Ranciato