[3-24]Fake News: the View from Natural Language Generation

文章来源:  |  发布时间:2017-03-22  |  【打印】 【关闭


  Title: Fake News: the View from Natural Language Generation 

  Speaker: Professor Kees van Deemter, University of Aberdeen 
  Time: 2:00pm, Friday, March 24, 2017 (周五下午2:00) 
  Venue:Room 334, Building 5, Institute of Software, Chinese Academy of Sciences 



  Recent political upheavals have caused a global debate about the spread of “fake news” on social media and elsewhere: reports that look like news, but which are intentionally untruthful. Fake news is often distributed for political or commercial gain; a well-known example is how opponents spread news-like reports claiming that former US President Obama was not born in the USA (and, by implication, not a ligitimate US president). 

  The present talk will not address the (very interesting) computational challenges posed by fake news, but examine the underlying idea of “deviating from the truth”. First, I sketch the architecture of a typical Natural Language Generation (NLG) system. Next, I show how each stage of the NLG pipeline has to make “debatable” decisions which can impact on the truth of the resulting text. Finally, I will use experiences in NLG to make some suggestions towards a systematic classification of deviations from the truth. This classification will allow us to discuss under what circumstances a deviation from the truth is permitted. 
  This is joint work with Ehud Reiter, also at the University of Aberdeen. 

  I am an academic working in Computational Linguistics. My main areas of expertise are Computational Semantics and especially Natural Language Generation. I've long taken an interest in logical and philosophical issues arising from this work; more recently I've collaborated extensively with psycholinguists interested in algorithmic models of human language production. 

  My research centers around computational models of human communication, and around applications of these models to practical problems (e.g., automatically explaining "big data" in human language). One of my specific research interests is the computational generation of referring expressions, as when we say 'the inventor of the light bulb', or 'the large icon at the top of your screen'. I am intrigued by situations in which communication is (or appears to be) flawed, as when we use expressions that are ambiguous or vague. Most recently I am starting to look at ambiguity and vagueness in Mandarin and I am looking for people who can collaborate with me on research in this area. 
  Ambiguity was the topic of the collection "Semantic Ambiguity and Underspecification" (CSLI Publications 1996). Vagueness is the focus of my book "Not Exactly: in Praise of Vagueness" (Oxford University Press 2010), which aims to reach people outside academia as well as within; in March 2016, a new Chinese translation of this book has appeared with Beijing Time-Chinese Publishing House. My book on Referring Expressions, entitled Computational Models of Referring: a Study in Cognitive Science" has appeared with MIT Press in June 2016.