Exploiting Linked Data to Build Web Applications
IEEE Internet Computing
The Role of Social Networking Services in eParticipation
ePart '09 Proceedings of the 1st International Conference on Electronic Participation
Twitter power: Tweets as electronic word of mouth
Journal of the American Society for Information Science and Technology
Characterizing debate performance via aggregated twitter sentiment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Towards a systematic exploitation of web 2.0 and simulation modeling tools in public policy process
ePart'10 Proceedings of the 2nd IFIP WG 8.5 international conference on Electronic participation
eParticipation initiatives in Europe: learning from practitioners
ePart'10 Proceedings of the 2nd IFIP WG 8.5 international conference on Electronic participation
Participatory design of public sector services
EGOVIS'10 Proceedings of the First international conference on Electronic government and the information systems perspective
Predicting the Future with Social Media
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Using Social Media to Predict Future Events with Agent-Based Markets
IEEE Intelligent Systems
A classification scheme for open government data: towards linking decentralised data
International Journal of Web Engineering and Technology
An activist lens for sustainability: from changing individuals to changing the environment
PERSUASIVE'13 Proceedings of the 8th international conference on Persuasive Technology
Exploring the use of new technologies in participation practices in legislation
Journal of E-Governance
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In the last years, several research endeavors were launched aiming at involving popular social media platforms in electronic participation. These early endeavors seem to present some essential limitations related mainly to scalability and uptake. In order to avoid these limitations, we introduce a two-phased approach for supporting participatory decision-making based on the integration and analysis of social and government open data. The proposed approach is based on the literature related to the analysis of massive amounts of social data for future events prediction. In this paper we also present a Web data driven architecture for the implementation of the proposed approach. The architecture is based on the use of linked data paradigm as a layer that will enable integration of data from different sources. We anticipate that the proposed approach will (i) allow decision makers to understand and predict public opinion and reaction about specific decisions; and (ii) enable citizens to inadvertently contribute in decision-making.