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SUMMARY:What can online collaborative dictionaries tell us about language 
 and social dynamics? - Barbara McGillivray (The Alan Turing Institute/Univ
 ersity of Cambridge)
DTSTART:20171109T110000Z
DTEND:20171109T120000Z
UID:TALK95299@talks.cam.ac.uk
CONTACT:Mohammad Taher Pilehvar
DESCRIPTION:Traditional dictionaries aim at including neologisms and new w
 ord senses\, and are regularly updated\, but they require enough textual e
 vidence for inclusion and are often slow at reacting to linguistic innovat
 ion. On the other hand\, online crowd-sourced dictionaries like Urban Dict
 ionary (UD) and Wiktionary are unique sources of data for studying this ty
 pe of language change as it happens\; they are constantly updated and the 
 threshold for including new material in them is lower than for traditional
  dictionaries. However\, this comes with additional challenges. UD tends t
 o record ephemeral quotidian spoken language and to represent popular view
 s of meaning to a greater extent than other dictionaries. Slang and offens
 ive language are over-represented in UD and its content often reflects the
  concerns of a specific community rather than wide linguistic trends. In t
 his talk I will report on preliminary results of a study conducted in coll
 aboration with Dr Dong Nguyen and Dr Taha Yasseri where we analysed UD dat
 a crawled in 2016 to answer the following questions: \n\n- What is the dis
 tribution of entries in UD and how do they compare with Wiktionary? \n- To
  what extend can UD be a reliable source for recording lexical-semantic ch
 ange in the\nEnglish language?
LOCATION: SR-24\, English Faculty Building\, 9 West Road (Sidgwick Site)
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