1,878 research outputs found
Agriculture as a source of fuel prospects and impacts, 2007 to 2017
Resource /Energy Economics and Policy,
EVALUATING THE IMPACTS OF AN INCREASE IN FUEL-ETHANOL DEMAND ON AGRICULTURE AND THE ECONOMY
Fuel ethanol demand is projected to increase because of proposed ban on methyl tertiary butyl ether (MTBE) in gasoline, renewable fuels standard, and the revised eight-hour ozone standards. In this paper, several scenarios of increased fuel ethanol demand and its effects on crop and feed prices, farm income and state finances under current tax-subsidy structure, are analyzed using a multi-sector econometric model AGMOD.Resource /Energy Economics and Policy,
Crisis Communication Patterns in Social Media during Hurricane Sandy
Hurricane Sandy was one of the deadliest and costliest of hurricanes over the
past few decades. Many states experienced significant power outage, however
many people used social media to communicate while having limited or no access
to traditional information sources. In this study, we explored the evolution of
various communication patterns using machine learning techniques and determined
user concerns that emerged over the course of Hurricane Sandy. The original
data included ~52M tweets coming from ~13M users between October 14, 2012 and
November 12, 2012. We run topic model on ~763K tweets from top 4,029 most
frequent users who tweeted about Sandy at least 100 times. We identified 250
well-defined communication patterns based on perplexity. Conversations of most
frequent and relevant users indicate the evolution of numerous storm-phase
(warning, response, and recovery) specific topics. People were also concerned
about storm location and time, media coverage, and activities of political
leaders and celebrities. We also present each relevant keyword that contributed
to one particular pattern of user concerns. Such keywords would be particularly
meaningful in targeted information spreading and effective crisis communication
in similar major disasters. Each of these words can also be helpful for
efficient hash-tagging to reach target audience as needed via social media. The
pattern recognition approach of this study can be used in identifying real time
user needs in future crises
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