Web 人口統計による小規模人口の発見
Discovery of Small Area Population through Web Demographics
T. Edwin Chow
Department of Geography
Texas State University
chow@txstate.edu
Geographic information provided by crowdsourcing (e.g. open street map), social
media, and data from Information and Communication Technology are useful sources ofbig data which can contribute to the development and understanding of a specificspatiotemporal landscape concerning an unknown population. However, the inherent
anonymity of these crowd-sourced or crowd-harvested data sources lack the socioeconomic
and demographic attributes to examine human dynamics and patterns revealed from thedata. In this paper, we investigate an Internet-based demographic data source, personal
microdata databases on the World Wide Web (hereafter web demographics), as potential
sources of aspatial and spatiotemporal information regarding the landscape of humandynamics. The objective of this paper is to explore their geographic and demographic
patterns (Figure 1).
People search engines, such as WhitePages (www.whitepages.com), gather
personal-level microdata (hereafter web demographics), including full name, address, age,phone number and household members. This research highlights the emergence of web
demographics as a new form of demographic data that are made searchable on the Internetby people finder sites like WhitePages. Based on surname analysis, it is possible to use
surnames that are highly predictive to an ethnic group to solicit their associated web
demographics and conduct a “web census” (Chow et al., 2011). Comparing the spatial
pattern of web demographics collected in 2009 and Census 2000 data revealed
demographic trends that conform to general understanding of spatial demography,
including the urban-to-suburban and rural-to-urban migration in major metropolitan areasof Texas. As web demographics contain personal level microdata, the spatial and temporal
resolutions can be flexible for space-time demographic research.

Using web demographics of Vietnamese-Americans in Texas collected in 2010 as acase study, this paper: 1) identifies small area population through the application of a CostSensitive Alternative Decision Tree (CS-ADT) algorithm, 2) analyze the demographic
characteristics of small area population and the functional relationship with travel distance,and 3) investigates migration pathways and clusters to include both short- and long-distancepatterns. By linking the physical space at the individual level, this unique methodology
attempts to enhance the understanding of the spatial distribution and dynamic pattern ofsmall area population at multiple spatial scales (Chow, 2013).

Figure 1. The spatial distribution of Vietnamese-American in Austin, Texas at the block level and theirdemographic structure.

References
Chow, T. E., 2013. "We know who you are and we know where you live": A research
agenda of web demographics, Crowdsourcing Geographic Knowledge. Volunteered
Geographic Information (VGI) in Theory and Practice. Edited by Sui D., S. Elmwood
and M. Goodchild, (Springer). pp. 265-285.
Chow, T. E., Y. Lin, &W. D. Chan. 2011, The Development of a Web-based Demographic
Data Extraction Tool for Population Monitoring, Transactions in GIS. 15(4): 479-494.