• DocumentCode
    1791779
  • Title

    On the coverage of science in the media: A big data study on the impact of the Fukushima disaster

  • Author

    Lansdall-Welfare, Thomas ; Sudhahar, Saatviga ; Veltri, Giuseppe A. ; Cristianini, Nello

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Bristol, Bristol, UK
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    60
  • Lastpage
    66
  • Abstract
    The contents of English-language online-news over 5 years have been analyzed to explore the impact of the Fukushima disaster on the media coverage of nuclear power. This big data study, based on millions of news articles, involves the extraction of narrative networks, association networks, and sentiment time series. The key finding is that media attitude towards nuclear power has significantly changed in the wake of the Fukushima disaster, in terms of sentiment and in terms of framing, showing a long lasting effect that does not appear to recover before the end of the period covered by this study. In particular, we find that the media discourse has shifted from one of public debate about nuclear power as a viable option for energy supply needs to a re-emergence of the public views of nuclear power and the risks associated with it. The methodology used presents an opportunity to leverage big data for corpus analysis and opens up new possibilities in social scientific research.
  • Keywords
    Big Data; data analysis; data mining; information analysis; Big Data; English-language online-news content; Fukushima disaster; association networks; corpus analysis; energy supply needs; narrative networks; nuclear power coverage; science coverage; sentiment time series; social scientific research; Association rules; Big data; Cancer; Diseases; Educational institutions; Media; Time series analysis; Computational linguistics; Data analysis; Knowledge discovery; Text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004454
  • Filename
    7004454