Extracting placeness from social media: An ontology-Based system

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The recent popularity of location-based social (LBS) networking services has resulted in huge volumes of geo-tagged data from social media, allowing us to monitor massive lifelogs from a real-world space. Also, the characteristics of urban areas, placeness, were identified from the lifelogs attained. Based on this concern, in this paper, we propose a new approach of placeness extraction with an ontology-based urban area placeness identification system. The suggested technique uses the textual, temporal, and spatial information of a LBS post from a specific area, and combines this information with the help of ontology. This combination measures the areas occasion-oriented placeness, which can be subdivided into time or companions. Our work focuses on a case study of Twitter data from the city of Seoul. The results show that our system is able to extract subdividable placeness and suitable correspondences when compared to real world socio-geographic features.
Publisher
Association for Computing Machinery, Inc
Issue Date
2017-08-01
Language
English
Citation

9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017, pp.644 - 651

DOI
10.1145/3110025.3116198
URI
http://hdl.handle.net/10203/281326
Appears in Collection
GCT-Conference Papers(학술회의논문)
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