This is a project about the tidytext library created for a college project for a text mining class.

Extracting positive and negative sentiments using tidytext package (for text analysis), janeaustenr package (for the dataset) and visualising the data using ggplot and wordcloud

Building a predictive model on Yelp airline reviews, and scoring similar Twitter comments. This is based on the book TidyText for R.

Text mining Wikipedia page of the following topics: Urban Planning, Architecture, Urban Design, Urban Economics. This exploratory text analysis was done as an assignment for Columbia GSAPP course: Exploring Urban Data with Machine Learning

A repository for R code that uses a fuzzy join operation to find scientific plant name matches in abstracts of scientific articles with the option of using parallel processing.

Text Sentiment Analysis Using R

R script to analyze two different music artist based on the words used in albums or songs. I have used geniusR library to gather the songs lyrics.

Coursera Data Science Specialization Capston project

Topic Modeling of US Presidential Speeches

Exploratory analysis on whatsapp chat text data. tidytext package

👍 😆 😭 ❤️ 😡 😯

Playing with the tidytext package and web scraping

Movie Summaries Analysis

text data analysis: differentiating anit- and pro-vaccination tweets

Analysis of questions asked in the Winter Session of the 17th Lok Sabha.

Here I keep my Deep Learning Projects

Text mining pop songs.

This repo contains my work and analysis for an intermediate R class (Fall 2022). My final project can be found here: https://byu1bg-michael-lewis.shinyapps.io/energy/