The `TweetTokenizer` is a part of the Natural Language Toolkit (NLTK) library in Python. It is specifically designed to tokenize tweets, which are often structured differently from standard English text. This tokenizer takes into consideration the unique characteristics of tweets, such as hashtags, mentions, URLs, and emoji. It helps to divide a tweet into individual tokens, such as words, hashtags, and emoticons, making it easier to analyze and process this type of text data. By using the `TweetTokenizer`, developers can efficiently tokenize, filter, and normalize tweets for various natural language processing tasks, such as sentiment analysis or topic modeling.
Python TweetTokenizer - 60 examples found. These are the top rated real world Python examples of nltk.tokenize.TweetTokenizer extracted from open source projects. You can rate examples to help us improve the quality of examples.