With all the World Cup excitement, I found myself wondering what the Twitter-scape looked like. Who is tweeting? What are they tweeting about? Where are they? What language are they tweeting in?
Obviously, such questions can apply to any tweet-worthy event. Along with the idly curious like me, various types of businesses from tech startups to local restaurants might want to know: What's my most vocal demographic? What time of day are people tweeting about my service most often? How do people feel about the new website?
Collecting all this data and analyzing it might seem like a big investment, but with the right tools it becomes trivially easy. In this article, I show you how to analyze tweet data using MongoDB as both the data store and the analytics engine. MongoDB has powerful analytics tools and straightforward pluggability into Hadoop for when you have a question that needs a more generic tool. I'm using tweets about the World Cup to demonstrate, but the concepts are generic and can be easily applied to your own data set.
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