Human Wildlife Conflict Monitoring: Understanding Human Wildlife Conflict Through Big Data

Benjamin Larsen, Ana Costa, McAllister Hall, Lantz McGinnis-Brown, Vanessa Fry

Research output: Other contribution

Abstract

This research examines global methodologies for understanding community attitudes and tolerance regarding Human Wildlife Conflict. Both traditional and future-focused approaches are examined for use in the World Wildlife Fund’s 13 tiger landscapes. Traditional methodologies are resource intensive and limit the ability for longitudinal studies and timely indication of attitudinal shifts. This research uses the Safe System Approach to explore innovative ways of understanding community attitudes toward human tiger conflict. We argue that improved monitoring of conflict areas will improve conflict management in all areas. This research uses policy analysis tools to evaluate the effectiveness of various big data techniques, including trend and sentiment analysis, network analysis and community leader identification. Piloting innovative approaches to understanding attitudes has great potential to expand knowledge of human tiger conflict and lead to conflict responses that can eliminate retaliatory killings of tigers globally.

Original languageAmerican English
StatePublished - 2020

Publication series

NameIdaho Policy Institute Reports

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