Opinion Mining, Analytics,

There has been significant research and practice oriented towards the rational exploitation of the rapidly expanding social media by private sector enterprises. However, much less research and practice have been done in this area with respect to the public sector. This paper explores advanced forms of rational exploitation of social media in government policy-making processes, aiming to strengthen and widen participation of and interaction with citizens, concerning new or existing public policies and services. The proposed approach is based on a platform, which can publish policy-related content and micro-applications towards multiple social media simultaneously, also collect data on citizens ’ interaction with them (e.g. views, comments, ratings, votes, etc.), using the application programming interfaces (API) of the targeted social media. The information gathered through social media will then undergo various types of advanced processing (e.g. access analytics, opinion mining, simulation modelling) in order to extract synthetic conclusions from them and provide substantial support to government policy-makers, always respecting data privacy guidelines. In addition, an extension of this ‘stimulated/ guided crowdsourcing ’ approach is presented, based on ‘non-moderated crowdsourcing ’ by government agencies. The above approaches allow a more advanced and rational exploitation of social media by government for supporting evidence-based decision and policy making