A summary of Chapters 1, 2, 3, 4, 5, 13, 16, 18 and 19 of the book of Easley and Kleinberg: Networks, Crowds, and Markets: Reasoning about a Highly Connected World.
Network: a pattern of interconnections among a set of things.
The social networks we inhibit have grown steadily in complexity due to technological advances global
communication and digital interaction.
The information we consume has a networked structure: understanding a piece of information depends on
understanding its relationship with other pieces of information in a large network of links, due to the increasing
amount of complexity in the structure.
Technological and economic systems dependent on networks of enormous complexity behavior increasingly harder
to reason about.
Objects in a network are connected by links. These links can define different forms of relationships or connections,
depending on the setting flexibility networks applicable in many domains.
Summarizing a network as a whole is hard, due to the interconnected parts: some are more or less densely connected,
others might form central cores.
Developing a language for talking about structures is an important step in understanding them.
Connectedness:
At the level of structure: who is linked to whom.
At the level of behavior: each individual’s actions have implicit consequences for the outcomes of everyone in
the system you should evaluate your actions not in isolation, but with the expectation that the world will
react to what you do.
Graph theory: the study of network structure focusing on social network analysis.
When analyzing social networks, one can identify strong ties, representing close and frequent social contacts, and
weak ties, representing more casual and distinct social contacts. There can be structural holes between parts of the
network that interact very little with each other.
Social networks can capture sources of conflict between a group by looking at non-interacting clusters within the
network theory of structural balance to reason about conflicts and their result on a network.
Game theory: provides models of individual behavior, depending on the behavior of others outcome of how a
group of people chooses to act depends on joint decisions made by all of them (eg. choosing a driving route, with the
amount of congestion dependent on how everyone chooses their route).
Interaction between people’s behavior can lead to counter-intuitive effects: Braess’s Paradox, where for example
adding resources to something to achieve greater efficiency, while it undermines its efficiency due to human behavior.
A collection of individuals must each commit to a strategy, thereby receiving a payoff, depending on the strategies
chosen by everyone. This framework allows us to make predictions of behavior, with as a fundamental part the
equilibrium: a state in which no individual is moved to change his/her strategy.
Interactions between buyers and sellers from a network network structure encodes pattern of trade.
Information online has a fundamental network structure Web search engines use the structure to determine the
prominence of a Web page, based on its position in the network.
While observing a large population over time, we can identify social practices: a recurring pattern by which social
trends are constantly emerging and evolving. People can choose to adopt or not new practices can become
popular or remain obscure and established practices can persist of fade over time. People influence other’s behavior
spreading new practices. There is a human tendency to conform, to behave as we see others behaving. This is
because behavior contains information. Decisions are made with this information one mimics other’s behavior
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