This paper extends demographers’ traditional approaches to estimating local populations using symptomatic data. We augmented those approaches in order to track one community’s de facto population—both its permanent residents (“Census population”) and other sojourners—and assorted others in residence for shorter spells of time (“impermanent residents”). We illustrate how a new type of mobility data—the anonymous “pings” emitted by people’s personal mobile devices—can unveil the presence and mobility patterns of de facto populations within a community by month, week, and day. We use these data to gauge the seasonal ebb and flow of population on Nantucket Island, MA, a seasonal resort community whose effective population far outnumbers its “Census population.” We distinguish the following factors: (1) Permanent Residents, for whom Nantucket is their “usual place of residence” and where one votes and files one’s tax return; (2) Commuting Workers, who reside off-island and regularly commute to jobs on-island via high-speed ferry or air taxi; and (3) Sojourners of three types: (a) Seasonal residents, most occupying a second home they either own or rent; (b) Seasonal workers, present for several months to fill many hospitality, landscaping, and other temporary jobs from April through September; and (c) Visitors, present for shorter stays, as vacationers or on business. For each segment, we highlight the estimation methodologies we devised and evaluate their strengths and limitations. Our research exemplifies the evolution of traditional demographic methodologies to address practical concerns at local community scales using “Big Data.” Resort communities and winter “snowbird” destinations in Sunbelt locales experience regular annual influxes of visitors and/or seasonal residents in particular months. Just as daytime urban populations strain downtown infrastructure and transportation, such impermanent residents—however, brief or lengthy their stay—impose seasonal strains on local infrastructure and public services.
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