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.
| Original language | English |
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| Title of host publication | Big Data (Big Data), 2014 IEEE International Conference on |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 60-66 |
| Number of pages | 6 |
| Publication status | Published - Oct 2014 |