Using Twitter Data to Compare the Popularity of 3 Programming Languages

Twitter is a rich source of useful information. It is a great tool for:

  • Researching Needs (for early customer development),
  • Tracking Trends (in your industry),
  • Watching Competition,
  • Finding  Influencers in your industry segment

We have been dabbling in some tools for mining Tweets and I am always on the look out for more.

There are a few kindred spirits who seem to be interested in similar topics. Here is one Scooped by Jose C Gonzalez. An Introduction to Text Mining using Twitter Streaming API and Python  by Adil Moujahid

Twitter data constitutes a rich source that can be used for capturing information about any topic imaginable. This data can be used in different use cases such as finding trends related to a specific keyword, measuring brand sentiment, and gathering feedback about new products and services.

In this tutorial, I will use Twitter data to compare the popularity of 3 programming languages: Python, Javascript and Ruby, and to retrieve links to programming tutorials.

This tutorial teaches you:an approach to mining tweets, analyzing them and visualizing them using simple open source tools. You will learn:

  • How to use a  Twitter Library for Python to find tweets on specific topics (in this case Python, Ruby, Javascript)
  • How to decode JSON, returned by the Twitter searches
  • How to use a Python library called Pandas to analyze Twitter Streams
  • How to use another Python library (matplotlib) to plot the results of analysis

 

 

 

 

 

 

 

 

 

 

 

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