NewsPanda: Media Monitoring for Timely Conservation Action

TL;DR

NewsPanda is an automated media monitoring toolkit that uses advanced NLP techniques to identify and analyze conservation-related news, significantly reducing human effort and enabling timely conservation actions worldwide.

Contribution

It introduces a BERT-based model with active learning and noise correction for effective media monitoring in environmental conservation.

Findings

Successfully deployed by WWF in multiple countries since 2022

Monitors over 80,000 websites and 1,074 conservation sites

Saves more than 30 hours of human effort weekly

Abstract

Non-governmental organizations for environmental conservation have a significant interest in monitoring conservation-related media and getting timely updates about infrastructure construction projects as they may cause massive impact to key conservation areas. Such monitoring, however, is difficult and time-consuming. We introduce NewsPanda, a toolkit which automatically detects and analyzes online articles related to environmental conservation and infrastructure construction. We fine-tune a BERT-based model using active learning methods and noise correction algorithms to identify articles that are relevant to conservation and infrastructure construction. For the identified articles, we perform further analysis, extracting keywords and finding potentially related sources. NewsPanda has been successfully deployed by the World Wide Fund for Nature teams in the UK, India, and Nepal since February 2022. It currently monitors over 80,000 websites and 1,074 conservation sites across India and Nepal, saving more than 30 hours of human efforts weekly. We have now scaled it up to cover 60,000 conservation sites globally.