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SUMMARY:Detecting Semantic Change Using LDA in Historical Texts: a Case St
 udy on Dutch  - Simon Hengchen (Université libre de Bruxelles)
DTSTART:20171010T120000Z
DTEND:20171010T130000Z
UID:TALK88721@talks.cam.ac.uk
CONTACT:Mohammad Taher Pilehvar
DESCRIPTION:Semantic change detection is relevant to many\, including hist
 orians who want to better understand their sources\, or lexicographers who
  wish to compile dictionaries. While the traditional way of detecting sema
 ntic change is to “read a lot” (Cavallin 2012)\, the availability of l
 arge diachronic corpora in digital form and computing power allow for a mo
 re automatic and efficient way to tackle this task. This talk is in two pa
 rts: first\, an LDA-based method to detect semantic change in historical\,
  dirty text will be presented\, and then a case study will illustrate the 
 approach. \nIn our case study\, we demonstrate a language-agnostic method 
 on a corpus of badly-OCRed Belgian socialist newspapers in Dutch from the 
 19th and 20th centuries. This case study thus hints at the reproducibility
  of the method on other\, less-resourced languages.\n\n\nCavallin\, K. (20
 12). Automatic extraction of potential examples of semantic change using l
 exical sets. In _KONVENS_\, pages 370–377\n
LOCATION: SR-24\, English Faculty Building\, 9 West Road (Sidgwick Site)
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