ABSTRACT
Tweets contain mentions of numerous entities, persons and events, and often additional information, like an opinion, that can be viewed as an annotation of that entity. However, this information is currently being accumulated only by specific applications without being made available in a generic format. We discuss a natural language processing approach to extract information about entities and their annotations from tweets and transform them into a semantic, reusable knowledge base. We believe this will greatly facilitate access to user-generated Twitter data for many applications.
- TwitterGlobalPR, http://twitter.com/twitterglobalpr/status/55779434350907392. Acc. 07-April-2011.Google Scholar
- L. Jiang, M. Yu, M. Zhou, X. Liu, and T. Zhao, "Target-dependent twitter sentiment classification" in Proc. of ACL-HLT. (2011). Google ScholarDigital Library
- T. Sakaki, M. Okazaki, and Y. Matsuo, "Earthquake shakes Twitter users: real-time event detection by social sensors" in Proc. of WWW. (2010). Google ScholarDigital Library
- M. De Choudhury, Y. R. Lin, H. Sundaram, K. S. Candan, L. Xie, and A. Kelliher, "How does the data sampling strategy impact the discovery of information diffusion in social media" in Proc. of ICWSM, (2010).Google Scholar
- K. Gimpel, N. Schneider, B. O. Connor, D. Das, D. Mills, J. Eisenstein, M. Heilman, D. Yogatama, J. Flanigan, and N. A. Smith, "Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments," in Proc. of ACL-HLT, (2011). Google ScholarDigital Library
- B. Han and T. Baldwin, "Lexical normalisation of short text messages: Makn sens a# twitter" in Proc. of ACL-HLT, ACL, (2011). Google ScholarDigital Library
Index Terms
- Extracting semantic annotations from twitter
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