Context Data set containing Tweets captured during the **3rd game of the 2018 NBA Finals** between **Cleveland Cavaliers** and **Golden State Warriors**. Content All Twitter APIs that return Tweets provide that data encoded using JavaScript Object Notation (JSON). **JSON** is based on key-value pairs, with named attributes and associated values. The JSON file include the following objects and attributes: * **[Tweet](https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/tweet-object)** - Tweets are the basic atomic building block of all things Twitter. The Tweet object has a long list of ‘root-level’ attributes, including fundamental attributes such as `id`, `created_at`, and `text`. Tweet child objects include `user`, `entities`, and `extended_entities.` Tweets that are geo-tagged will have a `place` child object. + **[User](https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/user-object)** - Contains public Twitter account metadata and describes the author of the Tweet with attributes as `name`, `description`, `followers_count`, `friends_count`, etc. + **[Entities](https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/entities-object)** - Provide metadata and additional contextual information about content posted on Twitter. The `entities` section provides arrays of common things included in Tweets: hashtags, user mentions, links, stock tickers (symbols), Twitter polls, and attached media. + **[Extended Entities](https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/extended-entities-object)** - All Tweets with attached photos, videos and animated GIFs will include an `extended_entities` JSON object. + **[Places](https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/geo-objects)** - Tweets can be associated with a location, generating a Tweet that has been ‘geo-tagged.’ More information [here](https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/intro-to-tweet-json). I also included the captured Tweets in a CSV file. In order to convert JSON data into a CSV file, I used the function `parseTweets()`. Acknowledgements I used the `filterStream()` function to open a connection to Twitter's Streaming API, using the keyword **#NBAFinals**. The capture started on **Thursday, June 7th 01:13 am UCT** and finished on **Thursday, June 7th 01:58 am UCT**. Inspiration - Time analysis - Try text mining! - Cross-language differences in Twitter - Use this data to produce a sentiment analysis - Twitter geolocation - Network analysis: graph theory, metrics and properties of the network, community detection, network visualization, etc.