Analyzing Web behavior in indoor retail spaces

Publication Year: 2017 Publication Type : JournalArticle


We analyze 18 million rows of Wi-Fi access logs collected over a one year period from over 120,000 anonymized users at an inner-city shopping mall. The anonymized dataset gathered from an optin system provides users’ approximate physical location, as well as Web browsing and some search history. Such data provides a unique opportunity to analyze the interaction between people’s behavior in physical retail spaces and their Web behavior, serving as a proxy to their information needs. We find: (1) the use of Wi-Fi network maps the opening hours of the mall; (2) there is a weekly periodicity in users’ visits to the mall; (3) around 60% of registered Wi-Fi users actively browse the Web and around 10% of them use Wi-Fi for accessing Web search engines; (4) people are likely to spend a relatively constant amount of time browsing the Web while their visiting duration may vary; (5) people tend to visit similar mall locations and Web content during their repeated visits to the mall; (6) the physical spatial context has a small but significant influence on the Web content that indoor users browse; (7) accompanying users tend to access resources from the same Web domains.


    author = {Yongli Ren and Martin Tomko and Flora Dilys Salim and Kevin Ong and Mark Sanderson},
    bibsource = {dblp computer science bibliography,},
    biburl = {},
    doi = {10.1002/asi.23587},
    journal = {J. Assoc. Inf. Sci. Technol.},
    number = {1},
    pages = {62--76},
    timestamp = {Mon, 02 Mar 2020 00:00:00 +0100},
    title = {Analyzing Web behavior in indoor retail spaces},
    url = {},
    volume = {68},
    year = {2017}


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