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The tutorial discusses the importance of ensuring quality input data for text analysis, starting with tokenization to identify potential issues. It introduces a dataset of almost three million Russian troll tweets from the 2016 US election cycle, focusing on the first 20,000 tweets and using metadata like followers and published date for analysis. The dataset is useful for tasks like topic modeling, classification, and named entity recognition. Tweets are expected to contain a lot of noise that needs to be addressed.
