2022-04-24

Objectives and Overview

  • Data collected from Julia Silge and David Robinson
  • Data are tweets from 2008 to 2017
  • Objective is to mine the tweets and analyze
  • Calculate word frequency and word use changes
  • Investigate frequent words for re-tweets and favorited tweets
  • Perform sentiment analysis and tf-idf analysis

Data Distribution of Tweets

Word Cloud for David and Julia

Word Frequencies

Comparing Word Use

Change in Word Use for David and Julia

Favorite Tweets and Retweets

Sentiment Analysis

Zipf’s Law

TF-IDF Model

Conclusions and Recommendations

  • Julia uses her Twitter for personal and professional development, while David uses Twitter for professional development mostly
  • David and Julia had their accounts for about the same amount of time, but Julia posted 4x as often
  • David mentions R Studio conferences and Julia mentions her family related topics
  • David sees sharp up ticks in word use and Julia has a negative trend with her word use changes
  • Sentiment analysis showed Julia had more positive attributions than David
  • Recommend investigating other RStudio content contributors