Python, sentiment analysis, R and Shiny
Blog post from Nylas
A detailed guide explains how to create a feedback system using Nylas Neural API's Sentiment Analysis to assess customer feelings about a product. The process involves building a Python-based web application using Flask to collect feedback, which is then emailed and stored in a SQLite Database. Feedback emails are processed with a Python script utilizing Sentiment Analysis to extract sentiment, ratings, and dates, which are subsequently visualized in a Shiny Dashboard using R. The guide provides step-by-step instructions, including setting up necessary environments, installing relevant packages, and creating required scripts and HTML templates, to facilitate the entire feedback and analysis workflow locally.
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