Using GDELT Data to Evaluate the Confidence on the Spanish Government Energy Policy

TitleUsing GDELT Data to Evaluate the Confidence on the Spanish Government Energy Policy
Publication TypeJournal Article
Year of Publication2016
AuthorsBodas-Sagi, D. J., and J. M. Labeaga
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
IssueSpecial Issue on Big Data and AI
Date Published03/2016

The growing demand for affordable, reliable, domestically sourced, and low-carbon electricity is a matter of concern and it is driven by several causes including public policy priorities. Policy objectives and new technologies are changing wholesale market design. The analysis of different aspects of energy markets is increasingly on the agendas of academics, firms’ managers or policy makers. Some concerns are global and are related to the evolution of climate change phenomena. Others are regional or national and they strongly appear in countries like Spain with a high dependence on foreign energy sources and high potential of domestic renewable energy sources. We can find a relevant case in Spanish solar energy policy. A series of regulatory reforms since 2010 reduce revenues to existing renewable power generators and they end up the previous system of support to new renewable generation. This policy change has altered the composition of the energy market affecting investment decisions. In this paper, we analyze the public opinion about energy policy of the Spanish Government using the Global Database of Events, Language, and Tone (GDELT). The GDELT Project consists of over a quarter-billion event records in over 300 categories covering the entire world from 1979 to present, along with a massive network diagram connecting every person, organization, location, and theme to this event database. Our aim is to build sentiment indicators arising from this source of information and, in a final step, evaluate if positive and negative indexes have any effect on the evolution of key market variables as prices and demand.

KeywordsBig Data, Electricity, Energy, GDELT, Public Opinion
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