/Twitter-Analysis-of-the-Microsoft-30DaysOfLearning

An analysis of the 30 days Microsoft learning twitter engagements

Twitter-Analysis-of-the-Microsoft-30DaysOfLearning

Front Page

Project Objective

To analyze the twitter engagement of the Microsoft 30 days of learning that took place between May 15 and June 19.

Data Source

The data was scraped from twitter using scrapy(a python library) on python.

Steps

    • 1) The data was scraped from twitter using scrapy(a python library) on python.
      2) The data was saved as a CSV file and then imported into Microsoft PowerBI.
      3) The data was then thoroughly cleaned to make it easy for analysis.
      4) Models were created, and meaningful insights drawn.
      5) Finally, I visualised the data and created a dashboard to tell the story in the most comprehendible way using PowerBI.

    • Visualizations

    Insights

    • 1) Most tweets were made from Android devices.
      2) The user with the twitter handle, @Theoyinbooke had the most tweets during this period.
      3) A total of 680 tweets were made made within this time period from 205 distinct twitter users.
      4) Wednesday is the day of the week which users tweet the most.