Linked Activity Spaces: Embedding Social Networks in Urban Space - Computational Approaches for Urban Environments - page 310

Fig. 13.2 The aspatial social network is visualized with a force-directed method that places nodes
in feature space based on their density of linkages in the Gephi computing environment (Bastian
et al. 2009 ). Larger nodes denote higher degree and smaller nodes indicate smaller degree

13.3 Methods

13.3.1 Creating Activity Spaces

To represent how the user moves in a city such as Jiamusi, we build activity spaces
(e.g. Axhausen et al. 2002 ; Axhausen 2007 ) that likely encompass a user's home,
work, and “third places” (Ahas et al. 2009 ; Schneider et al. 2013 ). We choose a
polygon method in order to represent the area surrounding the cell towers where
the user is likely to be found, since he or she uses the nearby towers. This polygon
will also likely encapsulate the areas that are convenient for a user to travel between
work and home.
These activity spaces summarize a user's set of frequently visited points (e.g.,
cell towers) by an ellipse that encapsulates 68 % (i.e., one standard deviation) of
points visited by capturing points that are concentrated in the center and neglecting
sparse points in the periphery (as in Carrasco et al. 2006 ). Ellipses are first centered
on the mean geometric center of a user's tower locations (mean of x coordinates and
y coordinates; repeating values are allowed if a user visits towers more than once).