1. The document discusses social network theory (SNT) and how it relates to Google. SNT analyzes relationships between individuals or objects and sees networks as having emergent behaviors. It began in psychology and sociology and focuses on describing social structures. 2. Google's search engine, PageRank, is based on SNT principles by analyzing the web as a social network of linked pages. PageRank assigns importance values to pages based on the importance of the pages linking to them. This personalized search using a user's social network. 3. The document predicts that Google could apply SNT more in its driverless cars and maps. Cars could form dynamic carpools based on users' social networks. Maps could

1. Running head: SOCIAL NETWORK THEORY AND GOOGLE 1
Social Network Theory and Google
Edward M. Alonzo, III
University of Florida

2. SOCIAL NETWORK THEORY AND GOOGLE 2
Social Network Theory and Google
I. Theory summary
Social Network Theory (SNT) began as a series of supplements to other theories (Prell,
2012 p.35). As late as 1972, proponents of SNT denied that it was its own theory. Mitchell
quoted Barnes as saying “there is no such thing as a theory of social networks; perhaps there will
never be” (as cited by Prell, 2012 p. 35). SNT began in psychology, sociology, social
anthropology and mathematics (Prell, 2012, p. 20). And it came unto its own with Harrison
White at Harvard in the 1960s and 70s (Prell, 2012, p. 19)
SNT focuses on the relationships of individuals and the whole network (Grosser &
Borgatti, 2013). Over its evolution individuals has been abstracted to the concept of a node
(Westaby, Pfaff, & Redding, 2014, p. 7). And taking a concept from Gestalt psychology, SNT
believes that networks have behaviours which can not be fully explained by the sum of
individual nodes (Prell, 2012, p. 21).
SNT can find precursors in Mass Society theory which had a focus on the social order
(Braddock, 2015a). Especially the theories of Tonnies and Durkheim in the late 1800s (Prell,
2012, p. 37). Tonnies coined Gemeinschaft and Gesellschaft which dealt with types of social
links (Prell, 2012, p. 37; Braddock, 2015c). Durkheim studied what he termed Mechanical and
Organic Solidarity which described social phenomena that were greater than the individuals
involved (Prell, 2012, p. 37; Braddock, 2015c).
One of the first branches of Social Network Theory, Sociometry, began in the 1930s by
J.L. Moreno (Prell, 2012, p. 21). The focus of Sociometry is to use quantitative methods to

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record and analyze the structure of small groups (Prell, 2012, pp. 21-22). The second branch,
Social Network Analysis, began in the 1950s and focused on studying the networks themselves.
Around this time in 1954, J. A. Barnes coined the term “Social Network” (Grosser & Borgatti,
2013, p. 3, Prell, 2012, p. 34). And in 1967 Stanley Milgram proposed degrees of
interconnectedness in his article “The Small World Problem” (Milgram, 1967; Ilhan, Gündüz-
Öğüdücü, & Etaner-Uyar, 2014). Some other important influences upon SNT were Lazarsfeld,
Simmel, Festinger, and Radcliffe-Brown amongst others (Prell, 2012).
Structural Balance was added to SNT in the 1940s and 50s and became a method for
predicting the evolution of a social grouping (Prell, 2012, pp. 26-27). The concept extended
relationships between nodes by describing relationships as positive or negative (Prell, 2012, p.
26). And these positive or negative relationships would ultimately seek balance instead of
imbalance (Westaby et al., 2014 p. 9).
Homogeneity, the similarity of nodes, and Performance of the node, in regard to some
outcome, are measures within SNT (Grosser & Borgatti, 2013, pp. 5-6; Westaby et al., 2014 p.
19). In addition to analyzing the individual aspects of a network (the node or individual, dyad or
relationship between pairs, and the network as a whole) (Grosser & Borgatti, 2013, p. 5; Prell,
2012) SNT takes two primary perspectives in gathering data. Those perspectives are egocentric
and whole network approaches (Grosser & Borgatti, 2013, p. 7). Egocentric starts with
individuals and defines the ties the nodes have, whereas whole-network starts with some group
and seeks to gather information from that population (Grosser & Borgatti, 2013, pp. 7-8; Prell,
2014, p. 43)

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SNT has been used in studies of small groups, conflict, resolution, communication
efficiency, work productivity, married couples, social action, friendship, (Prell, 2014) politics
(Westaby et al., 2014), social networking services, and even search engines (Ilhan et al., 2014).
II. Evaluate
Within SNT, the working epistemology is Social Constructivism (Braddock, 2015c) in
that the network only exists within a social construct. And the nature of the network can infer
value (or social capital) to the links and nodes (Page, Brin, Motwani, & Winograd, 1999).
SNT’s axiology tends to value balance over imbalance (Prell, 2012) or tension reduction
(Westaby et al., 2014, p. 9). But because of it’s primarily descriptive nature, SNT is mostly
value-neutral or even value agnostic, which has been a criticism of SNT (Westaby et al., 2014, p.
9). The ontology is pragmatic “created by individuals who are actively negotiating life”
(Braddock, 2015c), with relationship behaviour usually seen as as temporary states that can be
reactional (Prell 2013, p. 39). Though Kozlowski, Gully, Nason, and Smith argue that SNT
“views networks as static” and that the temporary state view is a new development (as cited in
Westaby et al., 2014, p. 11).
SNT’s ontology can be either Individual or Social Construct weighted. But both are
aspects of SNT (Grosser & Borgatti, 2013, pp. 7-8; Prell, 2014, p. 43). SNT is context sensitive,
in that a particular social network context is the basis of analysis. And SNT appears that it can be
actional or non-actional in perspective depending upon the researcher’s interest.
It is a Post-Positivist theory because it is often used to “explain, predict and control”
(Braddock, 2015c) networks and behaviour. But it is also partly a hermeneutical/Interpretive
theory because it tries to model how people understand the world through relationships.

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Goodness
Scope, Appropriateness, Heuristic Value, Validity, Parsimony, Openness, Practicality,
and Testability are aspects which can be used to evaluate the goodness of a theory (Braddock,
2015c).
The scope of SNT has expanded from individuals to all networks of objects (Westaby,
Pfaff, & Redding, 2014, p. 7). And as such can be limitless in application and is thus high in
Heuristic Value. SNT maintains a high level of logical consistency (appropriateness) due to its
analytical and sociometric upbringings. Though there is some debate on this, as Hafner-Burton,
Kahler and Montgomery in 2009 criticised SNT as it “assum[es] rather than demonstrat[es] the
causal mechanisms [of network constraint and enabling of members]” (as cited in Westaby et
al., 2014 p. 9).
As for validity, SNT does describe social networks, but this is also one of its criticisms as
being “overwhelmingly descriptive in nature”( Westaby et al., 2014 p. 9). This descriptiveness is
also where SNT is most practical as it has been used repeatedly to model all kinds of
relationships in the real world. Yet the predictivity of SNT seems to be important only to those
interested in structural balance. And this is an area that needs more development. SNT is
foundationally simple as graphs and mathematics are often used to illustrate a given system
(Prell, 2012). But due to its evolution as supplementary to other disciplines (Prell, 2012 p.35)
there appear to be no universally accepted foundational statements. Except perhaps the call by
Radcliffe-Brown in the 1940s and 50s to quantify and analyze social networks (Prell, 2012, pp.
29-30). So SNT’s Parsimony can vary depending upon which thread you wish to study.
SNT is quite open and has grown into its own theory because of this openness. As
mentioned before, SNT came about because of additions/supplements to other disciplines (Prell,

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2012, p. 35). And revolution is not unheard of, as can be attested to by its varied application from
individuals to web pages (Page et al. 1999; Ilhan et al. 2014). SNT is testable in that you can
record actual relationships and their outcomes. You can also compare social capital (e.g., as
measured by PageRank) to actual importance (e.g., as measured by Usage) to find out how well
the system describes reality (Page et al. 1999, p. 13). And you can use both of these methods to
improve models.
Overall, SNT seems to be a good theory that provides new insight into network
constructs. It is interesting as it addresses a greater idea than the parts that comprise it. And it has
a long history that involves collaboration from many disciplines and people. And as mentioned
before it is still very relevant to timeless and modern concerns (Page et al. 1999; Prell, 2012).
But as said before, SNT probably needs to develop more predictivity.
III. Google
The Google company was founded in 1998 and was based on the Google search engine
that Sergey Brin and Larry Page created while at Stanford in 1996 (Google, n.d.a). Since then
the company has expanded to include Gmail, Google Plus, Google Maps, Google Earth,
YouTube, Android, Adwords, Google Docs, Self-Driving Cars, wearables and more (Google,
n.d.c, Google; n.d.d).
Google passed Exxon as the #2 US company, by valuation, in 2014 and remains there
(Solomon, 2014; iWeblists, 2015). Google also remains #2 out of all tech companies in the
world. (PwC, 2014) Google in an international company now and has over “70 offices in over
40 countries” (Google, n.d.b). And it currently employs more than 53,000 people (Google, 2014)
17 years after they hired their first employee in 1998 (Google, n.d.c).

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Google is known for its motto “Don’t Be Evil” which was suggested by Paul Buchheit
around 2000 (Fung, 2014; Gibbs, 2014; Abbruzzese, 2015). The Motto and the mission
statement which the concept was incorporated into (Google, n.d.e) were created to set it apart
from companies like Microsoft. Microsoft at the time was fighting an antitrust case and was seen
as “exploiting the users” (Abbruzzese, 2015). Google’s first thing they “know to be true” is to
“focus on the user and all else will follow” (Google, n.d.e). Which means that they develop
products with a focus on how they will serve the user, rather than their bottom line (Google,
n.d.e).
IV. SNT and PageRank
Social Network Theory is one method of describing the structure of World Wide Web.
Nodes are web pages and hypertext links are descriptors of the relationships in the network
(Page, Brin, Motwani, & Winograd, 1999, p. 3). Search engines use these relationship links to
measure the importance, or social capital, of a given page (Page et al., 1999, p. 2). But because
the web is “free of quality control or publishing costs” it is easy to manipulate the Social
Network by creating new pages (Page et al., 1999, p. 1).
What was novel about Google’s approach is that it, in addition to counting the number of
links, added a social capital measure called PageRank (Page et al., 1999, p. 2). The net PageRank
of the web is considered constant and each page is given its PageRank by the pages that link to it
(Page et al., 1999, pp. 3-4). The system is first described by copying all the links and
URLs(pages) to a database (Page et al., 1999, p. 7). Once it is described you can then run the
PageRank algorithm. The algorithm then assigns PageRank values to each URL (Page et al.,
1999, p. 7). And it splits the value of given page evenly to the pages that it links to (Page et al.,

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1999, p. 4). So that a page simultaneously gives value to and receives value from other pages
(Page et al., 1999, p. 4). Then over many iterations of the algorithm the value of each page is
refined and the net values of all pages converge to the constant value(Page et al., 1999, p. 7).
The process could be sped up by giving initial values to pages instead of having the algorithm
figure it out without initial values. (Page et al., 1999, p. 7)
Or put another way, PageRank calculates the percent of total social capital that each page
has, based on the social capital of its relations. Added into this social capital equation is capital
based on the page’s actual usage, or visits (Page et al., 1999, p. 11). Thus PageRank “represent[s]
a collaborative notion of authority or trust” (Page et al., 1999, p. 11).
Another aspect of SNT that PageRank uses is customizing the social network of web
pages according to a particular person or entity (Page et al., 1999, p. 11). These “personal search
engines” takes the egocentric approach instead of a whole network approach. It starts with a
specific node, finds its relations and gives social capital to other nodes based on what is
important to the first node (Page et al., 1999, pp. 11-12). Page et al. suggest that “these search
engines could save users a great deal of trouble by efficiently guessing a large part of their
interests given simple input such as their bookmarks and homepages” (1999, p. 12).
Google currently uses over 200 different signals to understand what a searcher is looking
for (Search Engine Land, 2010a). And Google was hoping in 2010 to expand to using more
social network service signals to personalize search even more (Search Engine Land, 2010b).
And Google claims that this social data would be voluntarily given (Search Engine Land,
2010b). I imagine that the social signals have been implemented and that the data probably
depends upon cookies and services that users are logged into.

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Given that there are approximately 3.5 billion Google searches in a day (Internet Live
Stats, 2015), Google’s PageRank is perhaps the most frequently used implementation of SNT in
history.
V. Make Predictions
I imagine that Google uses some form of SNT in the software of its driverless cars and
Google maps. But I think these are two places that can benefit greatly from an even stronger
usage of SNT.
Driverless cars
Google’s driverless cars probably maintain some sort of representation of all the objects
on the road and the particular car’s relation to them. This kind of social network data seems
necessary to maintain safe distances and navigation. But a more complex social network could
do more than just getting a car from point a to b. Google could implement a personalized social
network based on the occupants of a particular car. This network would be able to identify
relations (e.g., friends or co-workers) this occupant has and modify the cars behaviour to those
relationships.
For example, could you imagine stepping out of your house and having a carpool car
arriving exactly as you exit? Carpools could be automated and dynamic so that everyone in your
company could be in it. The individual cars would pick up people on the most efficient route and
only those who were ready. It could thus prevent annoying delays and increase timeliness and
satisfaction. And if someone’s car broke down, the nearest carpool members could be
automatically recruited to pick the people up. And another car could be activated for service.

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Google Maps
Google’s Maps likely use some social network model to process the most efficient path
from one place to another. And it now incorporates real-time data of road conditions with
Google’s acquisition of Waze. This acquisition expands Maps’ social network model’s to include
more social data and predictability (Lunden, 2013).
And though Bardin said “What search is for the web, maps are for mobile” (as cited in
Lunden, 2013), I think maps could also be for more desktop driven search. I can imagine a time,
when I start looking for a new apartment, enter in my price range and several points of interest
(work, school, church and family) and have the search engine propose several on-the-market
apartments that will minimize my travel times and meet my budget. Google already does
something similar, by suggesting nearby restaurants when you search for a food or restaurant
type. But using saved real-time data from actual road conditions to predict what locations would
work best for commuting could dramatically increase the happiness of users. And Google can
use the data it already has on us to make a good part of the process automated.
VI. Extend
SNT has been criticised as static and purely descriptive (Westaby et al., 2014, pp. 9,11).
And I would argue that it is unidimensional or planar in describing a group. And I think this is an
artifact of the way sociometry began, selecting a specific group for a specific analytic purpose.
But as Page et al. have demonstrated (1999) you can add additional data and layers to an SNT
model to make it more descriptive of reality and responsive to individual nodes’ preferences.
And I think SNT could benefit from a big data approach, by creating countless signals
and layers for each node and relationship, so that the model is no longer limited by what can be

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easily visualized and managed by hand. A big data approach could also automate identifying
important signals and gathering of data. Much like the google search engine does through
crawling the graph (Page et al., 1999).
Another weak spot for SNT is one that Google identified (Page et al., 1999, p. 13). And
that was that PageRank was not a completely accurate predictor of real world social capital
because there are some relationships that go unreported. The example that they point out is
pornography “because people do not want to link to pornographic sites” (Page et al., 1999, p.
13). This points out a flaw in SNT because SNT assumes that all relationships are reported.
Whereas from the experience of comparing PageRank to site usage (by looking at cached data),
PageRank and usage did not necessarily correlate in areas that relationships might not be
reported.
Using a big data approach and automation, SNT could compare current and past states of
a given network, thus eliminating the need for reporting. This would help the SNT to more
accurately reflect the real world and could help predict the evolution of a network and its bonds
over time. Thus improving the descriptiveness and predictiveness of the theory as a whole.

12. SOCIAL NETWORK THEORY AND GOOGLE 12
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