Wenxiao Hu

Collaborated on a project analyzing global energy policy design and its impact on environmental performance using R. We employed text mining to assess policy names and topic modeling to identify trends. Our analysis included LASSO regression to explore the relationship between energy budgets and the Climate Change Index. The findings offer valuable insights for policymakers on how language and budget priorities influence environmental outcomes and support decarbonization efforts. -Data Collection and Text Mining: Analyzed the impact of energy policy design on environmental performance across 26 countries (2020-2022) using R, including budget and diction analysis. -Topic Modeling: Tokenized policy names using R, identified 951 key terms related to energy policies, and applied topic modeling to extract potential themes. -LASSO Regression for Policy Impact: Performed LASSO regression to assess the relationship between energy budget allocation and the Climate Change Index, highlighting correlations with renewable energy investment. -Data Visualization: Created word clouds and bar charts to visualize keyword trends and policy shifts over time, presenting insights into policy emphasis and performance.