The social mood reader: Mapping citizen engagement using the semantic web and supercomputing
Actual experiments in e-government and participatory online decision-makinghave, however, often proved disappointing. Traditional forms of governmentpolicy making and political organization, based upon centralised andhierarchical structures, one-to-many communications, and ‘push’ models ofstate–citi...
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| Format: | Conference Paper |
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ANZCA
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/49361 |
| _version_ | 1848758224668327936 |
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| author | Balnaves, Mark |
| author2 | A. Henderson |
| author_facet | A. Henderson Balnaves, Mark |
| author_sort | Balnaves, Mark |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Actual experiments in e-government and participatory online decision-makinghave, however, often proved disappointing. Traditional forms of governmentpolicy making and political organization, based upon centralised andhierarchical structures, one-to-many communications, and ‘push’ models ofstate–citizen interaction, have struggled to adapt to the decentralised, manyto-many forms of interaction of the Internet (Flew & Young 2005).Flew and Young’s quote above gets straight to the point. Participatory online decisionmakinginvolves more than consultation or sophisticated ways of delivering information tocitizens, although these of course are important. Online decision-making presupposes asocial-organisational structure that makes real decision-making possible. In this paper theauthor provides an overview of the use of sophisticated semantic web tools to calculatecitizen mood and the kinds of organisational structure emerging in local governmentjurisdictions that allow for actual decision-making. |
| first_indexed | 2025-11-14T09:40:36Z |
| format | Conference Paper |
| id | curtin-20.500.11937-49361 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:40:36Z |
| publishDate | 2011 |
| publisher | ANZCA |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-493612018-04-18T00:55:00Z The social mood reader: Mapping citizen engagement using the semantic web and supercomputing Balnaves, Mark A. Henderson Actual experiments in e-government and participatory online decision-makinghave, however, often proved disappointing. Traditional forms of governmentpolicy making and political organization, based upon centralised andhierarchical structures, one-to-many communications, and ‘push’ models ofstate–citizen interaction, have struggled to adapt to the decentralised, manyto-many forms of interaction of the Internet (Flew & Young 2005).Flew and Young’s quote above gets straight to the point. Participatory online decisionmakinginvolves more than consultation or sophisticated ways of delivering information tocitizens, although these of course are important. Online decision-making presupposes asocial-organisational structure that makes real decision-making possible. In this paper theauthor provides an overview of the use of sophisticated semantic web tools to calculatecitizen mood and the kinds of organisational structure emerging in local governmentjurisdictions that allow for actual decision-making. 2011 Conference Paper http://hdl.handle.net/20.500.11937/49361 ANZCA fulltext |
| spellingShingle | Balnaves, Mark The social mood reader: Mapping citizen engagement using the semantic web and supercomputing |
| title | The social mood reader: Mapping citizen engagement using the semantic web and supercomputing |
| title_full | The social mood reader: Mapping citizen engagement using the semantic web and supercomputing |
| title_fullStr | The social mood reader: Mapping citizen engagement using the semantic web and supercomputing |
| title_full_unstemmed | The social mood reader: Mapping citizen engagement using the semantic web and supercomputing |
| title_short | The social mood reader: Mapping citizen engagement using the semantic web and supercomputing |
| title_sort | social mood reader: mapping citizen engagement using the semantic web and supercomputing |
| url | http://hdl.handle.net/20.500.11937/49361 |