Python Tutorial: Understanding Twitter JSON

Want to learn more? Take the full course at https://learn.datacamp.com/courses/analyzing-social-media-data-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Great job! Now that you've collected some Twitter data, let's dig into the structure of the data. In the examples which we are working with in this course, the information is returned in Javascript Object Notation, or JSON. JSON is a special data format which is both human-readable and is easily transferred between machines. JSON is structured a lot like Python objects and is composed of a combination of dictionaries and lists. Understanding the Twitter JSON is critical to knowing how to analyze Twitter data. There's a lot of data in a single Twitter JSON. For instance, in a single original tweet -- that is, a tweet that's not a retweet or a quoted tweet, you have foundational information like the text, when it was created, and the unique tweet ID. You also have information like how many retweets or favorites it has at the time of collection, what language it's in, if it's a reply to a tweet and to which tweet, and to which user. More importantly, the Twitter JSON contains several important child JSON objects. These are like dictionaries stored in other dictionaries. The important ones which we'll cover in this course are user, place, and extended_tweet. user contains all the useful information you'd want to know about the user who tweeted, including their name, their Twitter handle, their Twitter bio, their location, and if they're verified. place contains information on the geolocation of the tweet, and we'll get into that in chapter 4. extended_tweet contains the full text of a tweet which is over 140 characters in length. When a tweet is a retweet or contains a quoted tweet, the whole of that tweet will be contained with the Twitter JSON. For retweets, that tweet will be stored in retweeted_status and for a quoted tweet in quoted