Abstract:Twitter allows users to easily post tweets on any subject or event anytime, generating massive amounts of rich text content on diverse topics. Automated methods such as Named Entity Recognition (NER) are required to process the massive tweet data. Processing tweets, however, poses a special challenge as they are informal posts with incomplete context and often contain acronyms, hashtags, misspellings, abbreviations, and URLs due to length constraints. This paper presents the first systematic study of NER in Ne… Show more
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