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.
翻译:非政府环境保护组织对于监测与基础建设工程相关的媒体并获取及时更新极为重要,因为这些项目可能会对关键保护区域产生巨大影响。然而,这种监测是困难且耗时的。我们介绍了NewsPanda,一个工具组,它可以自动检测和分析与环境保护和基础建设相关的在线文章。我们使用主动学习方法和噪声校正算法对BERT-based模型进行微调,识别与环境保护和基础建设相关的文章。对于已识别的文章,我们进行进一步的分析,提取关键词并找到潜在相关来源。自2022年2月以来,WWF(世界自然基金会)团队已经成功地在英国、印度和尼泊尔部署了NewsPanda。它目前监控着印度和尼泊尔的超过80,000个网站和1,074个保护区,每周节省了超过30个小时的人类工作量。我们已经将其扩展到全球60,000个保护区。