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Updated: Jul 9, 2025

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger
Published on: January 16, 2020
Tracking electricity losses and their perceived causes using nighttime light and social media
Samuel W Kerber1, Nicholas A Duncan1, Guillaume F L'Her1,2
1Department of Mechanical Engineering, The Colorado School of Mines, Golden, CO 80402, USA.
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 othe 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. Nighttime light data (in March 2019 for Caracas, Venezuela) are used to indicate blackout regions. Twitter data are 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 and Twitter activity. 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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