Andrea Ceron Fedra Negri

Public Policy and Social Media: How Sentiment Analysis Can Support Policy-Makers Across the Policy Cycle

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This article demonstrates that, in a «Big Data» world, comments of social media users can be used to support the action of policy-makers across all the steps of the policy cycle. It applies a modern technique of Supervised Aggregated Sentiment Analysis to three public policies introduced in Italy from 2012 to 2014: the abolishment of the public funding of political parties, the «jobs act» labour market reform and the «80 euros tax bonus». Results show that social media analysis can help policy-makers to accomplish the following tasks: 1) developing synthetic indicators that serve as «fire alarms» on relevant topics; 2) rating the available policy alternatives according to citizens' preferences; 3) monitoring citizens' behaviours and opinions during the implementation of a public policy.


  • Social Media
  • Sentiment Analysis
  • E-government
  • Responsiveness
  • Institutional Learning


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