Assessment of Online Deliberative Quality: New Indicators Using Network Analysis and Time-series Analysis

Research output: Contribution to journalArticleScientificpeer-review


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 languageEnglish
Article number1187
Issue number3
Number of pages21
Publication statusPublished - Feb 2021
MoE publication typeA1 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

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