In the last decade unprecedented wealth of digital (geographic) information has been made available to planners to support analysis, design and decision-making. On the one hand, developments in Spatial Data Infrastructures (SDI) (i.e. INSPIRE Directive 2007/02/EC in Europe) are fostering the access and reuse of authoritative Geographic Information (GI) according to common data, technology, and policy standards (Campagna and Craglia, 2012). On the other hand, advancement in geobrowsers and mobile technologies enabled citizens acting as volunteer sensors (Goodchild, 2007) to crowdsource GI real-time in a bottom-up fashion. More recently, widespread social media success favoured the diffusion of geo-referenced multimedia (Sui and Goodchild, 2011), or Social media Geographic Information (SMGI). The latter can be considered an innovative Big Data source, inasmuch as traditional data collection and spatial analysis techniques may be not fully suitable for eliciting the full knowledge potential out of them. Furthermore, this potential may be considered still limited for the public users both in terms of access and available analysis methods and tools. Accordingly new methods and tools should be developed. In the light of these premises, the authors present an assessment framework for social media data analysis methods and tools, with the aims of defining the current state of development as well as opportunities for decision-support in spatial planning. The poster illustrates the assessment framework, referring to real world case studies documented in literature and proposes an original methodology for social media data spatial analysis (i.e. spatio-temporal-textual analysis) developed by the authors, addressing pitfalls in existing practices.
Social Media Geographic Information: Current developments and opportunities in urban and regional planning
MASSA, PIERANGELO;CAMPAGNA, MICHELE
2014-01-01
Abstract
In the last decade unprecedented wealth of digital (geographic) information has been made available to planners to support analysis, design and decision-making. On the one hand, developments in Spatial Data Infrastructures (SDI) (i.e. INSPIRE Directive 2007/02/EC in Europe) are fostering the access and reuse of authoritative Geographic Information (GI) according to common data, technology, and policy standards (Campagna and Craglia, 2012). On the other hand, advancement in geobrowsers and mobile technologies enabled citizens acting as volunteer sensors (Goodchild, 2007) to crowdsource GI real-time in a bottom-up fashion. More recently, widespread social media success favoured the diffusion of geo-referenced multimedia (Sui and Goodchild, 2011), or Social media Geographic Information (SMGI). The latter can be considered an innovative Big Data source, inasmuch as traditional data collection and spatial analysis techniques may be not fully suitable for eliciting the full knowledge potential out of them. Furthermore, this potential may be considered still limited for the public users both in terms of access and available analysis methods and tools. Accordingly new methods and tools should be developed. In the light of these premises, the authors present an assessment framework for social media data analysis methods and tools, with the aims of defining the current state of development as well as opportunities for decision-support in spatial planning. The poster illustrates the assessment framework, referring to real world case studies documented in literature and proposes an original methodology for social media data spatial analysis (i.e. spatio-temporal-textual analysis) developed by the authors, addressing pitfalls in existing practices.
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