Real-time Insights from Social Media Data

- 1 minutes read - 95 words
  • Loaded and inspected data for topics that were hot worldwide (WW) and in the United States (US) at the moment of query
  • Used json.dumps() method to have the data formatted as a pretty JSON string
  • Used python’s set datastructure to find the common trends between “World Trends” and “US Trends”
  • Digged deeper to explore the common hot trend “#WeLoveTheEarth”
  • Performed frequency analysis to get the sense of the data and Extracted useful information from retweets
  • Manipulated and Visualized the data in a better and richer way
  • Analysed languages used in tweets

Link to GitHub Repository