Tracking electricity losses and their perceived causes using nighttime light and social media
October 18, 2023 Β· Declared Dead Β· π iScience
"No code URL or promise found in abstract"
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Authors
Samuel W Kerber, Nicholas A Duncan, Guillaume F LHer, Morgan Bazilian, Chris Elvidge, Mark R Deinert
arXiv ID
2310.12346
Category
physics.soc-ph
Cross-listed
cs.LG,
cs.SI
Citations
3
Venue
iScience
Last Checked
4 months ago
Abstract
Urban environments are intricate systems where the breakdown of critical infrastructure can impact both the economic and social well-being of communities. Electricity systems hold particular significance, as they are essential for other infrastructure, and disruptions can trigger widespread consequences. Typically, assessing electricity availability requires ground-level data, a challenge in conflict zones and regions with limited access. This study shows how satellite imagery, social media, and information extraction can monitor blackouts and their perceived causes. Night-time light data (in March 2019 for Caracas, Venezuela) is used to indicate blackout regions. Twitter data is used to determine sentiment and topic trends, while statistical analysis and topic modeling delved into public perceptions regarding blackout causes. The findings show an inverse relationship between nighttime light intensity. Tweets mentioning the Venezuelan President displayed heightened negativity and a greater prevalence of blame-related terms, suggesting a perception of government accountability for the outages.
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