Date of Original Version
Proceedings of the Annual Meeting of the Association for Computational Linguistics
Copyright 2011 ACL
Abstract or Description
We address the problem of part-of-speech tagging for English data from the popular microblogging service Twitter. We develop a tagset, annotate data, develop features, and report tagging results nearing 90% accuracy. The data and tools have been made available to the research community with the goal of enabling richer text analysis of Twitter and related social media data sets.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.
Proceedings of the Annual Meeting of the Association for Computational Linguistics, 42-47.