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Measuring Geospatial Properties: Relating Online Content Browsing Behaviors to Users’ Points of Interest

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Abstract

With the growth of the Mobile Internet, people have become active in both the online and offline worlds. Investigating the relationships between users’ online and offline behaviors is critical for personalization and content caching, as well as improving urban planning. Although some studies have measured the spatial properties of online social relationships, there have been few in-depth investigations of the relationships between users’ online content browsing behaviors and their real-life locations. This paper provides the first insight into the geospatial properties of online content browsing behaviors from the perspectives of both geographical regions and individual users. We first analyze the online browsing patterns across geographical regions. Then, a multilayer-network-based model is presented to discover how inter-user distances affect the distributions of users with similar online browsing interests. Drawing upon results from a comprehensive study of users of three popular online content services in a metropolitan city in China, we achieve a broad understanding of the general and specific geospatial properties of users’ various preferences. Specifically, users with similar online browsing interests exhibit, to a large extent, strong geographic correlations, and different services exhibit distinct geospatial properties in terms of their usage patterns. The results of this work can potentially be exploited to improve a vast number of applications.

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Acknowledgements

This work is supported in part by the National Natural Science Foundation of China (61671078, 61601042), Funds of Beijing Laboratory of Advanced Information Networks of BUPT, Funds of Beijing Key Laboratory of Network System Architecture and Convergence of BUPT, and 111 Project of China (B08004).

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Authors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Qiujian Lv

  2. Research Center of Network Monitoring and Analysis, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China

    Yuanyuan Qiao, Yi Zhang & Jie Yang

  3. Decisions, Networks and Analytics Laboratory, Swedish Institute of Computer Science, Stockholm, Sweden

    Fehmi Ben Abdesslem

  4. Technology Research Institute, Aisino Corporation, Beijing, China

    Wenhui Lin

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  1. Qiujian Lv
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Lv, Q., Qiao, Y., Zhang, Y. et al. Measuring Geospatial Properties: Relating Online Content Browsing Behaviors to Users’ Points of Interest. Wireless Pers Commun 101, 1469–1498 (2018). https://doi.org/10.1007/s11277-018-5773-7

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