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Activity location inference of users based on social relationship

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Abstract

Users in social networks often form relationships with other users who participate together in various activities nearby. The activity locations which are frequently shared with the friends are important in real life in order to understand the precise spatial space of the social users. However, the locations of individuals in a social network are often unknown. This is because the social users do not bother to broadcast their locations in public due to many reasons including privacy. Identifying the top activity location of a user at a higher granularity level will improve various community based applications like Meetup, Groupon, etc. In this paper, we propose a method to infer the top activity location of social users using the implicit information available in the network. Our proposed approach can estimate the activity location of a user by propagating the spatial information of the neighbors through friendship edges. We maintain a proper inference sequence to propagate the location labels of the users. We find that the proposed method has significantly improved the state-of-the-art network based location inference techniques in terms of both the accuracy and efficiency.

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Authors and Affiliations

  1. The University of Western Australia, Perth, Australia

    Nur Al Hasan Haldar & Mark Reynolds

  2. CSIRO Data61, Perth, Australia

    Quanxi Shao & Cecile Paris

  3. Deakin University, Marsfield, Australia

    Jianxin Li

  4. China University of Geosciences, Wuhan, China

    Yunliang Chen

Authors
  1. Nur Al Hasan Haldar
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  2. Mark Reynolds
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  3. Quanxi Shao
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  4. Cecile Paris
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  5. Jianxin Li
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  6. Yunliang Chen
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Correspondence to Nur Al Hasan Haldar.

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Haldar, N.A.H., Reynolds, M., Shao, Q. et al. Activity location inference of users based on social relationship. World Wide Web 24, 1165–1183 (2021). https://doi.org/10.1007/s11280-021-00899-y

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  • DOI: https://doi.org/10.1007/s11280-021-00899-y

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