A simple Shiny application written in R that visualizes Twitter data.
This performs a Twitter search (by term or user), runs a sentiment analysis on the tweets, and a principle component analysis for the 100 most common terms (other than the search term). Visualizations are avalable for the sentiments and the PCA by themselves and as a function of time. Also returns a table sampling tweets based on their PCA values.
This was produced as part of the Essentials of Data Science workshop I attended in 2016 (now hosted by Byteflow Dynamics). This code is not actively maintained, but feel free to grab a copy if you'd like to run or modify it.