Linked Activity Spaces: Embedding Social Networks in Urban Space - Computational Approaches for Urban Environments - page 323

investigating residents' accessibility to amenities (such as hospitals), travel time to
work, and social justice issues such as susceptibility to industrial and environmental
hazards (Cutter et al. 2003 ). In addition to these variables, we should emphasize the
importance of social capital within the city.
We cannot infer these social patterns from city form, or social networks alone
as the connection between these variables is statistical and likely scale dependent.
Thus, our task with this chapter was to illustrate how the linked activity space
method allows for the integration of information from a social network into
geographic space, a combination that is rarely investigated in detail (Andris 2011 ).
Although we use a call dataset record (CDR) for our analysis, this method can
be employed to any dataset that has both evidence of social ties between agents and
the geo-location of the agents. Other mechanisms for telecommunications (such as
Skype, Google Video/Chat, Viber, and Whats-App) can be substituted for mobile
phone calls. If these data are available, it may be worth considering the combination
of the CDR dataset for interesting results on which modes of communication are
popular in general, or in certain parts of the city, or during certain time frames.
We may be able to capture the growth of one mode over another, over a longer
time period. One exciting prospect is to see which neighborhoods make more
international calls, or calls to other cities.
We do find a number of methodological and pragmatic challenges to this type of
research. Many of these challenges stem from the nascent state of big data analysis
that will perhaps become more reliable and complete in the future. Nevertheless,
there are issues with these data that can be addressed: CDR datasets do not capture
an ego with alters who do not appear in the social network. Multiple cell phones
per person and multiple people per cell phones do not ensure that the telephone
number is a proxy for an individual's communication patterns. Without figures on
the provider's market penetration rate is difficult to understand friendships via calls
to users who use a different provider. We also note a number of subjective decisions
in creating a meaningful sample, such as the minimum number of towers frequented
in order to be included in the dataset, the number of seed users, and number of friend
“levels” to draw from the networks. None of these issues is a fundamental limitation,
so we look forward to future datasets that can overcome some of these difficulties.
We hope to see more research on the integration of social networks and urban spaces
in the future as a unique window into how urban form and social function shape each
other.

Acknowledgments This research was partially supported by the Army Research Office Minerva
Program (grant no. W911NF-121A 0097), the John Templeton Foundation (grant no. 15705),

the Bill and Melinda Gates Foundation (grant no. OPP1076282), the Rockefeller Foundation, the
James S. McDonnell Foundation (grant no. 220020195), the National Science Foundation (grant
no. 103522), the Bryan J. and June B. Zwan Foundation, and the University of Georgia.