Part-of-Speech Tagging for Twitter : Word Clusters and Other Advances

  title={Part-of-Speech Tagging for Twitter : Word Clusters and Other Advances},
  author={Olutobi Owoputi and Brendan F O’CONNOR and Chris Dyer and Kevin Gimpel and Nathan Schneider},
We present improvements to a Twitter part-of-speech tagger, making use of several new features and largescale word clustering. With these changes, the tagging accuracy increased from 89.2% to 92.8% and the tagging speed is 40 times faster. In addition, we expanded our Twitter tokenizer to support a broader range of Unicode characters, emoticons, and URLs. Finally, we annotate and evaluate on a new tweet dataset, DAILYTWEET547, that is more statistically representative of English-language… CONTINUE READING
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