Conservation is fundamentally about human behavior. Protecting biodiversity and mitigating climate change requires that stakeholders across different sectors and societies cooperate and act. My work has used data science techniques ranging from the local scale, focused on interviewing resource users in tropical Asia, to the global scale of social media to elucidate the social, economic, and ecological factors that shape human interactions with nature. I will discuss several case studies that highlight how text analyses and online “Big Data” can generate powerful new insights for conservation and social-ecological systems research. I will discuss work that performs a systematic characterization of environmental personas on social media, using natural language processing to geolocate users and evaluate their views toward the environment. I will discuss how these findings can drive new approaches for conservation messaging and engagement. Finally, I will show how large language models can be used to synthesize and map evidence for natural climate solutions at a global scale.