  The number of standardized policy documents regarding climate policy and
their publication frequency is significantly increasing. The documents are long
and tedious for manual analysis, especially for policy experts, lawmakers, and
citizens who lack access or domain expertise to utilize data analytics tools.
Potential consequences of such a situation include reduced citizen governance
and involvement in climate policies and an overall surge in analytics costs,
rendering less accessibility for the public. In this work, we use a Latent
Dirichlet Allocation-based pipeline for the automatic summarization and
analysis of 10-years of national energy and climate plans (NECPs) for the
period from 2021 to 2030, established by 27 Member States of the European
Union. We focus on analyzing policy framing, the language used to describe
specific issues, to detect essential nuances in the way governments frame their
climate policies and achieve climate goals. The methods leverage topic modeling
and clustering for the comparative analysis of policy documents across
different countries. It allows for easier integration in potential
user-friendly applications for the development of theories and processes of
climate policy. This would further lead to better citizen governance and
engagement over climate policies and public policy research.
