Database Reference
In-Depth Information
Table 16.1
Summary of Typical Properties of Mobility Data from GSM, GPS, and
Geo-Social Network Sources (Real-World Scenarios may Differ Depending
on the Application).
Source
Public Volume Per User
Accuracy
Privacy Sensitive
Social Layer
GPS
No
High
1cm
Yes
No
GSM
No
Low to high
100m
Yes
Yes
Geo-social nets
Yes
Low to moderate
1cm to 1m
No
Yes
accuracy of the data, whether the data should be considered as sensitive for pri-
vacy reasons (in online social networks usually the data are sparse and provided
intentionally by the users, bringing this type of data to a reasonably nonsensible
status), and the social dimension (i.e., there exists a social connection between
two users). Clearly, given the above characteristics, the tasks of analysis to
be performed on the different data are very different, and each task should be
conducted on the most appropriate data. For example, assessing the validity of
an urban transportation system using online social network data may provide
inappropriate results, as the data do not contain enough and precise information.
16.4.3 CGI Retrieval from Geo-Social Networks
While GPS and GSM data are typically collected by private entities, tele-
com providers or citizens storing their trajectories on their personal devices,
geo-social data are characterized by being publicly available on social media
platforms. All major geo-social networking systems offer access to their huge
corpus of data via several Web APIs (“application programming interface”).
Many developers have created and made freely available libraries that do a lot
of the heavy lifting needed to interact with the APIs, allowing researchers and
data analysts to reconstruct and explore portions of social graphs and users'
movements. An API provides methods to access almost every feature of the
system, and is typically defined as a set of HTTP request messages along with
a definition of the structure of response messages (usually in an XML or JSON
format). Each API is in constant evolution and represents a facet of the system,
allowing developers to integrate specific functions or to build upon and extend
their applications in new and creative ways. However, as regards the download-
ing of data, it presents some limitations due to compliance with privacy policies
or the management of server load. Such restrictions define the level of detail and
accuracy with which is possible to get data. We present a quick discussion of
the API challenges of three very popular geo-social networks.
Twitter, for example, currently provides three APIs. Two of them offer
methods to access status data and user information (name, profile, following/
