rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Gary King on big data analysis
  name:
    name part: King, Gary
    name part: 1958-
    role:
      role term: creator
    role:
      role term: speaker.
  name:
    name part: Edmonds, David
    name part: 1964-
    role:
      role term: host,
    role:
      role term: interviewer.
  type of resource: sound recording-nonmusical
  origin info:
    place:
      place term: enk
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (podcast (26 min., 10 sec.))
  abstract: About this Podcast: The data revolution is upon us. It's said that in the last two years, more data has been created than has ever been created before. And in two years' time, we'll be able to say the same thing. For Gary King, the Albert J. Weatherhead III University Professor and director of the Institute for Quantitative Social Science at Harvard University, it is not the growth in the volume of data which is changing the world, it is the ability to use it. King describes big data as "the change in the world in which lots of things produce data." This data itself is not inherently useful; the question is whether you can make it useful. In this conversation King uses text analysis as an example of big data analytics. Social media has likely brought with it the largest increase in the expressive capacity of the human race in the history of the world. Roughly 650 million social media messages are produced every day. So, to someone trying to make statements about what those messages contain, would having 750 million messages make anything better? "Having bigger data," King says, "only makes things more difficult." The real innovation is in the ways of analysing those data. King goes on to discuss the development of a sophisticated technique for analysing social media posts according to the needs of social scientists, valuing the trend of what people are saying over individual categorisations. He describes how a "mathematically similar" project, which utilised a database of Chinese social media posts, led to an insight into the how and why of Chinese government censorship, and to a further surprising revelation. After discussing the supposed failure of polls in predicting Trump's presidency, King concludes with a rumination on big data's characterisation as a democratising, or manipulative, force.
  target audience: specialized
  note: Gary King, speaker ; David Edmonds, interviewer.
  subject:
    topic: Big data
  subject:
    topic: Data mining
  subject:
    topic: Social media
  subject:
    topic: Data Mining
  subject:
    topic: Social Media
  subject:
    topic: Big data
  subject:
    topic: Data mining
  subject:
    topic: Social media
  classification: QA76.9.B45 G37 2017
  classification: 005.7
  related item:
    title info:
      title: Social Science Bites
  identifier: 9781526459824
  identifier: 1526459825
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: SGPBL
    record creation date: 190214
    record change date: 20241105204729.2
    record identifier: in00005517082
    language of cataloging:
      language term: eng