Introducing Textual Analysis Tools for Policy Informatics: A Case Study of E-petitions

Document Type

Conference Proceeding

Publication Date

2015

Keywords

policy informatics, textual analysis tool, natural language processing, named entity recognition, topic modeling, data mining, e-petition, policy analysis, social media

Digital Object Identifier (DOI)

https://doi.org/10.1145/2757401.2757421

Abstract

Electronic petitioning (e-petitioning) provides a unique and promising channel through which people can directly express their policy preferences. E-petitions may be viewed as a natural laboratory for determining subjects of public interest, and thus can be used by policy analysts to understand social needs and constraints. In this paper, we introduce textual analysis tools (such as NER and topic modeling) and extract three types of novel variables (informativeness, named entities, and 21 topics) from We the People petition texts. The regression result shows that informativeness, named location, and several topics are significantly correlated with the log of the signature counts. These exploratory but promising results indicate that textual analysis tools can complement traditional statistical methods by providing descriptive measures that are helpful for making causal inferences from electronic petition data. These new tools, we believe, will facilitate policy analysis and policy informatics by enabling meaningful use of large volumes of online archives containing public expression regarding policy preferences.

Was this content written or created while at USF?

No

Citation / Publisher Attribution

Proceedings of the 16th Annual International Conference on Digital Government Research, p. 10-19

Link to Full Text

Share

COinS