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.
@article{DBLP:journals/jasis/RenTSOS17,
author = {Yongli Ren and
Martin Tomko and
Flora Dilys Salim and
Kevin Ong and
Mark Sanderson},
bibsource = {dblp computer science bibliography, https://dblp.org},
biburl = {https://dblp.org/rec/journals/jasis/RenTSOS17.bib},
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 = {https://doi.org/10.1002/asi.23587},
volume = {68},
year = {2017}
}
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