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“Familiar strangers” in the big data era: An exploratory study of Beijing metro encounters
"غریبه های آشنا" در عصر داده های بزرگ: یک مطالعه اکتشافی از برخورد مترو پکن-2020 Traditionally, familiar strangers are defined as those we encounter and observe repeatedly in the city but never
interact with. They are common to most urban dwellers. They also have various socioeconomic, sociopsychological
and public-policy implications, which have only been sporadically mentioned and/or examined in
existing studies across different disciplines. In this manuscript, we first summarize fragmental existing studies on
familiar strangers that are defined in the traditional manner based on “small data” such as survey responses.
Then we reconceptualize “familiar strangers” against the backdrop of the emergence and increased availability
of big and open data. Such familiar strangers are called “familiar strangers in the big data era” (FSiBDE). After
this, we have done the following: (a) synthesized and hypothesized factors influencing the distribution and
quantity of the FSiBDE; (b) conducted an empirical study in the context of Beijing to embody and operationalize
a special type of the FSiBDE among metro riders and to study its possible influencers. We find that across metro
stations, it is spatial structure, population distribution, and transport network that significantly influence the
count and odds of FSiBDE among millions of metro riders. In addition, the FSiBDE also can have important policy
and planning implications for operating metro services and managing metro station. Keywords: Familiar stranger | Big data era | Implications | Odds | Distribution | Beijing |
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