| Title |
Physical-Cyber-Social Similarity Analysis in Smart Cities |
| ID_Doc |
44284 |
| Authors |
Farajidavar, N; Kolozali, S; Barnaghi, P |
| Title |
Physical-Cyber-Social Similarity Analysis in Smart Cities |
| Year |
2016 |
| Published |
|
| DOI |
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| Abstract |
The inter-departmental interactions and coordination of resources are two essential components for realising a smart city platform. In this study, we investigated citizens' role in enhancing and facilitating the delivery of services by merging three key aspects of the smart city research field, namely Internet of People, Internet of Things and Web of Data. To this end, we developed a hybrid approach to extract meaningful information and to find physical-cyber-social similarity in smart cities. The three specific data sources used in this study were Twitter, road traffic disruptions collected from Transport for London API, and events parsed from Time Out London. With the proposed hybrid approach, we found that 49.5% of the Twitter traffic comments are reported approximately five hours prior to the authority's official records. Moreover, we discovered that amongst the pre-scheduled sociocultural events topics; transportation, cultural and social event topics are 31.75% more likely to influence the distribution of the Twitter comments than sport, weather and crime topics. |
| Author Keywords |
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| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000399698600084 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications |
| Research Area |
Computer Science |
| PDF |
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