NewsPanda: Media Monitoring for Timely Conservation Action


  • Sedrick Scott Keh Carnegie Mellon University
  • Zheyuan Ryan Shi Carnegie Mellon University 98Connect
  • David J. Patterson World Wide Fund for Nature
  • Nirmal Bhagabati United States Agency for International Development
  • Karun Dewan World Wide Fund for Nature
  • Areendran Gopala World Wide Fund for Nature
  • Pablo Izquierdo World Wide Fund for Nature
  • Debojyoti Mallick World Wide Fund for Nature
  • Ambika Sharma World Wide Fund for Nature
  • Pooja Shrestha World Wide Fund for Nature
  • Fei Fang Carnegie Mellon University



Conservation, Infrastructure, NLP


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.




How to Cite

Keh, S. S., Shi, Z. R., Patterson, D. J., Bhagabati, N., Dewan, K., Gopala, A., Izquierdo, P., Mallick, D., Sharma, A., Shrestha, P., & Fang, F. (2023). NewsPanda: Media Monitoring for Timely Conservation Action. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 15528-15536.



IAAI Technical Track on deployed Highly Innovative Applications of AI