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A Socio-Geographic Perspective on Human Activities in Social Media
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Building, Energy and Environmental Engineering, Energy system.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.ORCID iD: 0000-0002-2337-2486
2017 (English)In: Geographical Analysis, ISSN 0016-7363, E-ISSN 1538-4632, Vol. 49, no 3, p. 328-342Article in journal (Refereed) Published
Abstract [en]

Location-based social media make it possible to understand social and geographic aspects of human activities. However, previous studies have mostly examined these two aspects separately without looking at how they are linked. The study aims to connect two aspects by investigating whether there is any correlation between social connections and users' check-in locations from a socio-geographic perspective. We constructed three types of networks: a people–people network, a location–location network, and a city–city network from former location-based social media Brightkite and Gowalla in the U.S., based on users' check-in locations and their friendships. We adopted some complexity science methods such as power-law detection and head/tail breaks classification method for analysis and visualization. Head/tail breaks recursively partitions data into a few large things in the head and many small things in the tail. By analyzing check-in locations, we found that users' check-in patterns are heterogeneous at both the individual and collective levels. We also discovered that users' first or most frequent check-in locations can be the representatives of users' spatial information. The constructed networks based on these locations are very heterogeneous, as indicated by the high ht-index. Most importantly, the node degree of the networks correlates highly with the population at locations (mostly with R2 being 0.7) or cities (above 0.9). This correlation indicates that the geographic distributions of the social media users relate highly to their online social connections.

Place, publisher, year, edition, pages
2017. Vol. 49, no 3, p. 328-342
National Category
Other Social Sciences Other Civil Engineering
Identifiers
URN: urn:nbn:se:hig:diva-24868DOI: 10.1111/gean.12122ISI: 000405108800004Scopus ID: 2-s2.0-85011710648OAI: oai:DiVA.org:hig-24868DiVA: diva2:1134008
Note

Funding agency:

Key Laboratory of Eco Planning & Green Building, Ministry of Education (Tsinghua University), China

Available from: 2017-08-17 Created: 2017-08-17 Last updated: 2017-08-17Bibliographically approved

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CiteExportLink to record
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