In this book, we will analyze social media data. We will harvest data from Twitter
(Appendix A), from Facebook and LiveJournal. We will learn to recognize online com-
munities, and study the anatomy of a viral video and a flashmob.
However, I will show that SNA can be applied in many different ways. In this book,
we will look at the social media, but we will also look beyond social media. We shall
study the relationships between companies through investment networks and through
shared boards of directors. We will look inside an organization and discover how the
social network around the water cooler and lunchroom affects the company’s ability
to perform—and how a company could shoot itself in the foot by ignoring this. We
will look at campaign finance and discover how a single special-interest group can
control the outcome of an entire election. We will explore the world of terrorists, rev-
olutionaries, and radicals—from stories of the Khobar Towers bombing in 1998 and
the 9/11 attacks, to the recent uprising in Egypt. We shall look at the anatomy of fads
and trends—which are often mediated by Twitter and Facebook, but are offline phe-
nomena by nature.
I will show you that network data is everywhere—you just need to learn to recognize
and analyze it. And once you do, new insights and ideas shall follow.
Analyzing Relationships to Understand People and Groups
The science of Social Network Analysis (SNA) boils down to one central concept—our
relationships, taken together, define who we are and how we act. Our personality,
education, background, race, ethnicity—all interact with our pattern of relationships
and leave indelible marks on it. Thus, by observing and studying these patterns we can
answer many questions about our sociality.
What is a relationship? In an interpersonal context, it can be friendship, influence,
affection, trust—or conversely, dislike, conflict, or many other things.
Binary and Valued Relationships
Relationships can be binary or valued: “Max follows Alex on Twitter” is a binary rela-
tionship while “Max retweeted 4 tweets from Alex” is valued. In the Twitter world,
such relationships are easily quantified, but in the “softer” social world it’s very hard
to determine and quantify the quality of an interpersonal relationship.
A useful stand-in for strength of an interpersonal relationship is frequency of commu-
nication. Besides being objectively measurable, frequency of communication has been
found by scientists to reflect accurately on the emotional content, and amount of in-
fluence in a relationship. This would, of course, not be true in many contexts (and you,
my dear reader, are probably busy coming up with counterexamples right now)—but
in many cases, for the lack of better data, frequency of communication works.
2 | Chapter 1: Introduction
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