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This project contains notebooks to introduce users to get tweets and use twitter endpoints using many use-cases.

The functionality of the notebooks are as follows:

  1. Crawler.ipynb - This tutorial introduces basic transactions such as getting a user's tweet, getting a user's followees, accessing a tweet with an id and searching for tweets containing specific words.

  2. Listen_for_important_events.ipynb - The goal of this tutorial is to introduce how to use the filtered stream and sample stream endpoints.

  3. NYC_Parking.ipynb - The goal of this tutorial is to introduce how to get tweets from specific twitter handles, search tweets for relevant information, and send messages based on contents of the tweets.

  4. filtering_tweets_by_location.ipynb - The goal of this tutorial is to show how to filter tweets based on their geographic location

  5. historical_tweets.ipynb - The goal of this tutorial is to show how to use the search-recent and full-archive search endpoints that allows users to access recent tweets with the search_recent endpoint and tweets dating all the way back to the beginning of twitter with the search_all_tweets endpoint.

  6. measure_tweet_performance.ipynb - The goal of this tutorial is to show how to get metrics such as the number of retweets, likes, replies, etc that can help you measure the performance of tweets.

  7. pos_tagger.ipynb - The goal of this tutorial is to introduce Part of Speech tagger for twitter data - http://www.ark.cs.cmu.edu/TweetNLP/ This tutorial has code from https://github.com/brendano/ark-tweet-nlp/

  8. tokenizer.ipynb - The goal of this tutorial is to introduce tokenizer for tweets - http://www.ark.cs.cmu.edu/TweetNLP/ This tutorial has code from https://github.com/brendano/ark-tweet-nlp/

  9. translating_plain_language_into_filtering_tweets.ipynb - The goal of this tutorial is to introduce how to convert rules from plain english into queries that can be used to filter your tweets.