Regular Expressions + Account Location metadata == Location Filtering
In my latest project, I explored the question, “What is the public sentiment in the United States on K-12 learning during the COVID-19 pandemic?”. Using data collected from Twitter, Natural Language Processing, and Supervised Machine Learning, I created a text classifier to predict Tweets' sentiment on this topic.
Since I wanted to hone in on sentiment in the United States, I needed to filterTweets by location. The Twitter Developer site offers some good guidance here on the available options.
I choose to use the Account Location geographical metadata. Here are the details from the Twitter Developer website: “Based on the ‘home’ location provided by the user in their public profile. This is a free-form character field and may or may not contain metadata that can be geo-referenced”.
Before we begin, here are a few caveats:
If those caveats are acceptable to you, keep reading. :)
Before I share the actual code, here’s a rundown of my methodology:
Now that I’ve shared the overall workflow let’s look at some code.
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