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.

通过利用 NewsPanda 的 BERT 模型进行环境保护和基础设施建设相关文章的自动检测和分析，减少了人力成本并有助于 NPO 更及时获得更新。