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A web app that lets you investigate the Twitter customer service of your service provider and see how it stacks up against the industry's best.
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01_convo_chains.ipynb
02_sentiment.ipynb
03_adding_sentiments_to_tweets_csv.ipynb
04_create_conversations_table.ipynb
05_creating_times_table.ipynb
06_averages_over_time.ipynb
07_interactive_results.ipynb
companies.csv
compconvlistdict_tofrom_csv.py
gcp_sentiment.py
readme.md
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readme.md

Twitter Customer Service Investigator

A web app that lets you investigate the Twitter customer service of your service provider and see how it stacks up against the industry's best. CLICK HERE to check to check it out!

In a nutshell

I used Natural Language Processing to analyze twitter conversations between mobile service providers and their customers to compute several customer satisfaction metrics for these companies over a period of three months. This information was used to build an interactive web app that allows a user to comprehensively compare the customer service of any provider with competitors and help them choose the best provider for their needs.

Project stages

Data collection, cleaning and restructuring

Feature Engineering and Analysis

Interactive web app

  • The quantitative results obtained from the data analysis were finally made accessible to the end user in the form of an interactive web app.
  • The interactive functionality was developed with Bokeh in 07_interactive_results.ipynb and the website was implemented with Flask.
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