In order to efficiently pursue environmental conservation, it is important for organizations to understand and obtain efficient updates on projects. Especially with the ever changing speeds of society and the countless actions being taken to solve the issue, it has become increasingly difficult to keep track of all the media and updates concerning conservation. Previously, NEWSPANDA, a toolkit, has benefited those looking to extract and analyze important online media concerning the topic of conservation. It has been successfully in use for over a year by the World Wide Fund (WWF), helping to efficiently deliver information on various conservation related topics in the UK, India, and Nepal. Hoping to broaden this research to further conservation sites in order to aid further efforts, this study will be expanding this framework to another language, Mandarin. This framework will first consist of using a BERT-based model to extract relevant articles concerning conservation and infrastructure construction. Then these most relevant articles will be further simplified using keyword analysis, the tracking of the topic over time, and geolocation. In using this framework, this study hopes to achieve a model that can be added to the existing toolkit to better the efficiency of workers in conservation organizations like WWF.