“…Computational text analysis is an emerging approach that allows the user to interact with unstructured text data through diverse techniques, such as frequency analysis, co-occurrence analysis, sentiment analysis, topic modelling, and those in natural language processing [203][204][205][206][207][208]. This approach has been used in research on public policy, for example, to study issue framing and agenda setting [209,210], map the relationship between policy discourse and public opinion [211], examine priorities of public agencies [212], "measure" policy design [213,214], and examine program evaluations [215]. In addition, it has been employed in research on energy and environment policy, illustratively, to understand stakeholder opinions regarding air pollution in Hong Kong [216], analyze 70 years of German parliamentary debate on coal [217], and identify various dimensions of electric vehicles' adoption in the United States using Facebook posts [218].…”