Abstract: Research background and purpose: Participatory budgeting (PB) plays an
important role in a city live. It strengthens democracy, improves transparency
of public expenditures, helps allocate resources more efficiently, and increases
civic responsibility. In order to assess how such a mechanism contributes
to public involvement and which initiatives are prioritized by the community
engaged in the participatory budgeting process, a pilot study was undertaken
for a selected Polish voivodeship city - Kielce. Attention was paid to the
category of winning tasks, considering the classification by project type and
its narrative.
Design/methodology/approach: The exploratory analysis was carried out on
real unit data. Data on projects submitted by residents were collected from
websites using web scraping tools. The article relies on the case-study method
as well as on the methods of quantitative and qualitative analysis. The narrative
data were explored with the assistance of machine learning technology –
Natural Language Processing (NLP) and the results were illustrated in the form
of a Word Cloud.
Findings: The conclusions of the picture of participatory budgeting in the
chosen city are decidedly positive. It is a tool that promotes democratization
of decision-making processes and involvement of citizens in public life. It is
significant that the local community opts for soft projects, particularly green
ones.
Value added and limitations: This study investigates the changes in citizen
engagement in PB using a time- and project-type-oriented quantitative
approach. Furthermore, a machine learning-based qualitative approach in
terms of NLP was employed to capture the major PB issues and topics, which
is rather absent in this research field. As a pilot study, this research is limited to
a single city and begins to explore text processing algorithms in such analysis.
The promising results suggest potential for research development in the
future.
DOI