Network theory: the bridge of new disciplines

Networks, differences, and pandemics

We have arrived at the WWW, nodes, Cybernetics, we still need to talk about page rank, algorithms, Artificial Intelligence, cookies, and Blockchain, but before that, let’s talk about the glue that holds everything together: the network, or rather, the concept of the network.

The story I want to tell you this month does not concern a single theory, but rather the ideal “place” of passage on which so many contemporary theories, from artificial intelligence to blockchain, rest their principles and concepts.

This is because many times those who approach these subjects believe that they are already ready, but in reality, they are the result of an acquired historicity and a world of scientists, philosophers of science, and intellectuals who have patiently transversely traveled the history of thought.

Epochal question.

Why are networks similar? Is our behavior the result of these similar networks? How do viruses spread? Why do we see similarities between earthquakes and financial crises?

We are immersed in a world in which the next project is tomorrow and the first goal is to do things well, not to grow or for any purely economic purpose, but for health, to leave a better world.

We have returned to recognizing the priority of a primary good. This is the worst crisis since World War II, as all world leaders have defined it. This crisis takes us back to when we asked ourselves about the plague in the Middle Ages.

Today, we understand what certain research incipits are. Where do the immense and formidable efforts of scientists start? We are acquiring a method that imposes the study of things “in a network.” In the form of connections.

However, this imposes another reflection: we should not take for granted the connections or links that allow us to reflect on where a crisis or pandemic comes from, let’s try to overcome any superficiality.

After talking in previous episodes about Euler and the so-called butterfly effect derived from Graph Theory, now we understand that the starting point for many experts, even as an unconscious procedure, passes through what we today better define as Network Theory.

That is, a way of seeing the connections, the passages, between various things, no longer broken down into small parts that are “indifferent” to each other, but as a complex path that allows these pieces to be put together to better understand the world through seemingly disconnected things.

One of its theorists and founders is Albert-László Barabási. A physicist, computer scientist, and researcher originally from Transylvania. I was lucky enough to attend some of his lectures and speak with him. In him, the transversality of knowledge is embedded and opened up. He put the Theory of Six Degrees of Separation into “formulas.” Let’s understand how.

Network and pandemic: the philosophy of relationships as a response.

• How do we study relationships in science?
• How do we move from the internet to new technologies?
• What similarities exist between pedestrian movement and bird flocking?
• What do queues at the supermarket checkout and long lines on the highway have in common?

The answer is the possibility of synchronous movement, which we call a Network! But which network? Not all networks are the same.

Let’s start with a fundamental misconception: everyone thinks that a network is a collection of things that have relationships with each other, all of which are the same. This is an unprecedented simplification. Human migration and bird migration are similar, but not the same.

Therefore, the first strong distinction to be made is that if we take a set A of objects that have an interconnection – the streets of a city, for example – and another set B – a flock of birds, for instance – it makes no sense to say that they are the same thing because they are made up of many parts. They are separate worlds.

Birds migrate every year, but this is not just “going and coming back”: there is a network. Certain populations that are migrating to Europe, on the other hand, pass from one state to another, which is quite different. They arrive and do not want to go back, and in their behavior there is nothing “natural,” as in the case of birds.

Why is a flock of birds (we see them circling for hours in the skies of many cities in the spring) a network? Because we see how the structure of flight is regulated by a flow of information that reaches each individual component.

Similar behavior is also found in some schools of fish – sardines, for example. One of the strangest things about flocks and schools is that everyone follows a leader who sets the course, but this leader changes continuously, lasting only a few seconds.

It’s as if there is a continuous passing of the baton, and the phenomenon is still largely unknown. If we think about the COVID-19 virus, do we not have the same sensation? And if we think about a terrorist cell?

So the answer to the question “why are networks so similar?” must be given with great caution. Many networks are not similar at all, as we have said. Others are. We note, for example, as mentioned above, that the spread of a biological or artificial virus and that of an information virus that spreads on the Internet possesses interesting similarities. And in fact, today, with the COVID-19 pandemic, we are studying the relationships between these two realities.

But beware! Everything changes, and profoundly, when we think that a virus is a living organism and that one of its most deadly behaviors is to modify itself during propagation; this is why sometimes it is tremendously difficult to find a vaccine.

An information virus today, such as fake news, moves with the same logic. Such logic is in the approach, but then differs based on automatisms that are unpredictable. We can only partially “cage” such unpredictability through algorithms that often become inefficient in a short time.

There is only one fundamental concept that brings all networks together, and that is the one that underlies Network Theory. For a long time, it was thought that the individual units that make up phenomena were at the root of all phenomena.

If I always look at the flock of birds and want to understand why it behaves that way, I have to study the individual.

It’s not like that: at some point with Barabasi it was understood that a crucial factor to study is the relationship between individuals.

In other words, two subjects, coming into contact, create a new phenomenon that is precisely their relationship. The behavior that individuals exhibit when they enter into a relationship is something that they wouldn’t have on their own. So, we must study relationships, and this means studying the network.

Forgetting individuals? No, absolutely not. Research must continually observe individuals and observe relationships. One of the two activities alone does not explain the phenomenon.

Societies, hubs, nodes, and links.

Individuals aggregate into societies. Societies have network structures. Network patterns and behaviors are useful for understanding the structures and dynamics of technological networks. The study and analysis of social networks in general serve as models for the analysis of social networks of any kind, from real communities of people to virtual communities of social networks.

On these premises is based social network analysis or SNA, a modern methodology for analyzing social relations used in sociology, anthropology, psychology, economics, management, to study phenomena such as international trade, the diffusion of information, the functioning of organizations, computing, and artificial intelligence, in a word, all fields where complex and interdependent phenomena arise among individuals and more or less numerous groups.

This same theory from which blockchain (ideally) was born and all the modern path of artificial intelligence.

Let’s understand better. Even to spread a more precise culture than those who often resort to terms such as nodes and hubs without knowledge. In the theory of social networks, society is studied as a network in which each individual (or actor) relates to others, modifying behaviors and knowledge reciprocally.

Society is the hub, the individual is the node, the relationships are the links. The set of hubs, nodes, and links constitutes the network.

• Hubs are large sorting centers, see international airports or high-voltage power cabins.
• Nodes are smaller sorting centers, such as minor airports and transformation cabins to provide energy to homes.
• Connections, also called “links,” occur when a point is connected to another thanks to a line: for airports, we think of stopovers, for energy, we think of the line between homes to provide energy to everyone.

These three elements are configured in architectures that respect specific rules and become complex networks, where the term complex means, paradoxically, intertwined but functional (https://marcosantarelli.eu/index.php/pubblicazioni-editoriali/19-marco-santarelli-news/37-equivalenza-flusso-sanguigno-e-rete-energetica).

• Society exists where a certain number of individuals interact with each other, interdependently.
• Links serve to transmit material and immaterial resources.
• Network models are structures with characteristics that favor or limit the activities of individual nodes.
• The social structure is made up of durable and recurring patterns of relationships among social actors.

The structure or topology of the network determines its behaviors, regardless of the scope of the network itself.

Networks, Study, and Science: The Keys to the Future.

Many times, when talking about intelligence, my area of expertise with logic and the philosophy of relationships, I have said that the future must take on this approach, not only as the distinctive character of certain behaviors, but also to evaluate their unpredictability.

I constantly speak of the intelligence of the future as understanding data, studying the computerization of sources, and now interconnected networks become and return to being important.

The same must apply to the approach to new technologies. We need a social approach that demonstrates to us that many things can easily escape mathematical structures, but also have a highly scientific and computerized approach that demonstrates how the discoveries of the world and science today are more valuable than ever.

Take the tree structure in mathematics, within this structure, there are networks that not only are a path between pairs of hubs, nodes, links, but they make sense in their interactions.

Monitoring the diffusion of information, as well as human relationships and the information that needs to be managed, makes research more meaningful and provides more answers. The center of gravity must be shifted, which, although including all the dynamics of known problems (from IT, cyber attacks, viruses, and terrorism), must be the engine, in which context analyses become time control diagrams (also every week or every day), establishing a process that is clearly exposed to numerous bifurcations.

It is therefore necessary to realize that, as in a game of chess, the unpredictable element leads to a broad field full of surprises. Although all the moves are known, there is always some surprise in human choices that can immediately send even the most mathematical bank crashing.

For example, an appropriate study of human distancing, social relationships in the coming years, and the logical understanding of the relationship between man and the world is needed, in short, what I would call the Philosophy of Relationships.

That is, the logical capacity of thought to combine the digital element with the human element and understand its landings or drifts. To better study, for a better approach to new digital forms of knowledge, information security, better understand the concept of Security by Design, collaborate and cooperate among multiple minds.

In short, to better cover the distance between man and things, try to give ourselves more possibilities. Intervene in the approach to modern technologies to reduce, as much as possible, the dangers.

On this line, one must think of a new topology, a mathematics of patterns and interactions in which logical elements of thought (inductive and deductive) interpenetrate with what I often call predictive intelligence and with a more cultural, human, and mathematical approach at the same time.

To understand the new control technologies well, one must first understand the chain that composes such technologies. For the next stories that I will tell you about page rank, algorithms, Artificial Intelligence, cookies, and Blockchain, this bridge launched today is a sentence from which we cannot exempt ourselves.