Abstract
This paper introduces a quantitative method for identifying newly emerging word forms in large time-stamped corpora of natural language and then describes an analysis of lexical emergence in American social media using this method based on a multi-billion word corpus of Tweets collected between October 2013 and November 2014. In total 29 emerging word forms, which represent various semantic classes, grammatical parts-of speech, and word formations processes, were identified through this analysis. These 29 forms are then examined from various perspectives in order to begin to better understand the process of lexical emergence.
| Original language | English |
|---|---|
| Pages (from-to) | 99-127 |
| Number of pages | 29 |
| Journal | English Language and Linguistics |
| Volume | 21 |
| Issue number | 1 |
| Early online date | 25 May 2016 |
| DOIs | |
| Publication status | Published - 1 Mar 2017 |
Bibliographical note
CORRIGENDUM: In the above mentioned article by Grieve, Nini & Guo, an error has occurred in the section numbering. Section 4 is missing and has been mistakenly labelled with section 5. All sections and subsections labelled section 5, should be section 4. Which means section 6 should be renamed section 5. DOI: http://dx.doi.org/10.1017/S1360674316000526Fingerprint
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