Abstract
Online deliberation research has recently developed automated indicators to assess the deliberative quality of much user-generated online data. While most previous studies have developed indicators based on content analysis and network analysis, time-series data and associated methods have been studied less thoroughly. This article contributes to the literature by proposing indicators based on a combination of network analysis and time-series analysis, arguing that it will help monitor how online deliberation evolves. Based on Habermasian deliberative criteria, we develop six throughput indicators and demonstrate their applications in the OmaStadi participatory budgeting project in Helsinki, Finland. The study results show that these indicators consist of intuitive figures and visualizations that will facilitate collective intelligence on ongoing processes and ways to solve problems promptly.
| Original language | English |
|---|---|
| Article number | 1187 |
| Journal | Sustainability |
| Volume | 13 |
| Issue number | 3 |
| Number of pages | 21 |
| ISSN | 2071-1050 |
| DOIs | |
| Publication status | Published - Feb 2021 |
| MoE publication type | A1 Journal article-refereed |
Fields of Science
- Helsinki
- big data
- deliberative quality
- governance
- indicators
- participatory budgeting
- resilience
- social network analysis
- throughput
- time-series analysis
- 1172 Environmental sciences
- 1181 Ecology, evolutionary biology
- 5142 Social policy