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Are “black swan” and “uncertainty” the same thing?

  Usually, the trajectory of a black swan is a power-law distribution, dragging a long tail, but the smaller the probability, the more impactful it is.
  Many times people often confuse “black swan” with “uncertainty”. For example, some people will regard the results of the US election as a “black swan”, especially when the word “black swan” is used too much in the reports of various agencies. , So that people are gradually paralyzed and ignore the real risk. When the real black swan came, he immediately panicked. Generally, the smaller the probability of the black swan, the more impactful it is. The “uncertainty” we often say is a random walk curve, and the maximum entropy distribution of randomness is a bell-shaped normal distribution, which can be predicted by the mean and variance. To put it bluntly, uncertainty can be predicted and managed, while the “black swan” is unpredictable and difficult to manage in advance.
  The overrated “black swan” and the underrated “black swan”
  Nasim Nicholas Taleb pointed out in his book “Black Swan” that the “black swan” is unavoidable because “we have What we don’t know is more important than what we know. This is the real reason for the Black Swan incident.” He used three characteristics to describe the “black swan event”: rarity, great impact, and seemingly predictable afterwards. Black swan is a rare and small probability event, even if there are some clues, it is often ignored. Once the critical point is passed, it is inevitable to erupt, and the impact is unusually difficult to resist.
  There are two kinds of “black swans” in Taleb’s eyes: “the black swan phenomenon that no one mentions” and “the black swan phenomenon in the narrative”. In reality, the probability of occurrence of the black swan phenomenon in the narrative is usually overestimated, while the risk of the real black swan is often underestimated. The real “black swans” are “no mention” because they are “because they do not conform to any model, and talking about them in public will make you feel ashamed because they look unreasonable.”
  However, the public opinion that accompanies the small-probability vicious event has become the “black swan in the narrative”. Taleb calls this black swan a “narrative fallacy”, and “after the fact” (rather than before) and “seemingly predictable” “It is precisely the motivation of the narration. Specious information, comments mixed with complex emotions, and various hindsight criticisms quickly mobilize people’s attention and emotional reactions, because human nature is keen on phenomena, imagination, cognition, memory, emotions and feelings. Mixed together, people usually prefer to spread their incompletely confirmed information, including more exaggerated descriptions, especially supported by some seemingly esoteric expert arguments and limited data.
  Dr. Sylvie Briand, director of the Department of Infectious Disease Management of the World Health Organization, called the public opinion after a major disaster an “information epidemic” (Infodemic). Information epidemic refers to the fact that too much information (some correct, some wrong) makes it difficult for people to find trustworthy sources of information and guidance that they can rely on, and may even harm people’s health. The “information epidemic” has a long history. In history, with the outbreak of every infectious disease, the “information epidemic” will break out at the same time. Especially in the early stage of the outbreak of infectious diseases, due to the unknown threat of new diseases, a large number of rumors and false information appeared. In the era of the Internet of Everything, with the help of the Internet and social media, the “information epidemic” spread to every corner of the world at lightning speed. However, the “information epidemic” was not born out of nowhere. It appeared because of various real worries and even panics in people’s hearts. At the beginning of the epidemic, relevant real information was severely lacking, and the information “vacuum” made people who were suffocated eager to capture information through various channels, so rumors and false information would come in. The spread of the disease and the spread of the information epidemic have similarities and some differences, but in any case, the path is rooted in the modern social network structure.
  Moments, random friends and super spreaders
  In 1967, American social psychologist Stanley Milgram put forward the famous “six degrees of separation” theory in “Psychology Today” magazine. From the theory of six degrees of separation, we know that in modern society, everyone can use a network of relationships to build relationships with strangers, and the path length is approximately equal to six. There are two types of friends in the small world network, “Clique friends” and “Random friends”. Although random friends are a kind of “weak relationship”, they can put any two people on the earth in six degrees. Established connections within, precisely because of the existence of these random friends.
  Next, let’s look at how infectious diseases and information epidemics use social networks to spread and spread from person to person. First, we divide the entire population into two categories: people who know or possess something (for example, disease and information) and people who don’t know or don’t own it. As time goes by, the thing will migrate between these two types of people, and its development curve is often concave (R-shaped) or S-shaped, and the shape of this distribution curve is determined by how people obtain information or It is determined by the disease. If people learn information from a single source or suffer from a disease, they will be R-shaped, and then spread through random contact to spread the disease in an S-shaped curve.
  From epidemiology, the spread of infectious diseases uses the SIR model (S means susceptible, I means infected, R means cured, as shown in Figure 2). If the SIR model is embedded in the network, it will be observed that the distribution of degrees is critical to the spread of infectious diseases. Usually the SIR model will produce a critical point, which is defined by epidemiology as the “basic reproduction number R0”, which is the ratio of the probability of contact multiplied by the probability of proliferation and the probability of recovery. For a certain infectious disease, if R0 is greater than 1, then this infectious disease can spread to the entire population, while infectious diseases with R0 less than 1 tend to disappear. Usually the Center for Disease Control guides policy making based on the estimate of R0 (Figure 3).
  At the tipping point, a small change in the nature of an infectious disease means a huge gap between failure and success. As long as R0 exceeds 1, its diffusion will show convexity and increase exponentially. When the first infected person is infected, he, as a central node, first connects to all other nodes through a hub-and-spoke network. Assuming that an infectious disease will randomly occur at a certain node, in the next period, the infectious disease may independently spread to each neighbor with a given probability corresponding to the power of the infectious virus. Randomly enter the new hub-and-spoke network through neighbors, which may serve as a central node or a peripheral node. If it serves as a central node, it can spread infectious diseases to any other node. If the peripheral node is infected, he may infect the central node. Once the new central node is infected, infectious diseases will inevitably spread. Epidemiologists refer to people on high-position central nodes (high-several nodes) as “superspreaders”. For infectious diseases, super-spreaders are not necessarily social stars or people with particularly wide connections, but may be engaged in a specific “one-to-many” occupation, such as cashiers, teachers, doctors, etc. Occupation allows him to randomly contact people who belong to different social networks. High-level nodes can not only spread infectious diseases faster, but also develop infectious diseases faster. If a person has three times as many friends as another person, his chance of contracting the disease is also three times that of the latter, and the probability of spreading the disease is also three times that of the latter. Therefore, his total contribution to the spread of infectious diseases will be 9 times that of another person.

  Even than the spread of the virus outbreak information quickly is
  to know, understand and control the “information epidemic” help people respond to disease outbreaks. In modern society, information is first broadcast in an R shape and then spread in an S shape. The biggest difference from the spread of viruses is that the spread of information does not require contact. The World Health Organization pointed out that in addition to viruses, “information epidemics” can also endanger health. First of all, a large amount of sad information will bring “empathy harm”, making people excessively influenced by emotions, losing reason and logic. Secondly, there are a large number of rumors mixed in the information. As unproven information, rumors can affect our moral judgment, and can also make us deceived and pay tangible or intangible costs. The Internet has gradually replaced traditional media as the main route of information dissemination, which makes the information epidemic even more difficult to prevent.
  Social interpersonal networks are mainly small-world networks, while the Internet is more like a scale-free network. The degree distribution of the small-world network is similar to that of the random network, and the connections between points are random. Small world networks have large clusters and small Hubs (central nodes). As the density increases, small world networks migrate into highly clustered networks, while scale-free networks migrate into high-level Hub networks, making scale-free networks have large Hub and small clusters. A scale-free network is a network composed of a small number of high-level nodes and a large number of low-level nodes. A small number of high-level nodes is called a Hub, which is a complex network with a power-law distribution. The dissemination model of the big Hub is the broadcast model first. The process of an information source disseminating information through the government, organization, enterprise, or even influential individuals is still an R-shaped curve. When the broadcasting model encounters a power-law distribution, the broadcasting of the Big Hub will cause the number of insiders to increase rapidly in a very short time, and the diffusion probability (Diffusion probability) is the product of the contact probability (Contact robability) and the sharing probability (Sharing probability) . For example, pop star Justin Bieber (Justin Bieber), as a big Hub, has an estimated R0 of 24, which means that his infectious “virulence” is stronger than that of a virus. When the insider produces random mixing in the interpersonal network (any two people in the relevant group have the same possibility of contact), the information begins to spread in the S-shaped diffusion model, and within a certain period of time, everyone in the relevant group will Master the information, and the speed of network propagation allows diffusion to be completed extremely quickly. It was not until almost everyone became an insider that the number of newly informed people decreased, thus forming the top (critical point) of the S-shape.
  Communication and control
  in the social field, since the receiver itself a choice, in the face “Information epidemic,” people have the right to informed choice. The challenge facing modern society is that there is too much information. Trustworthy communication channels can play an “amplifier” role in the circulation of information. In the period when many information related to the plague is unknown, it is also a critical period for controlling the outbreak of the epidemic. If you wait until the information is complete before communicating with the public, it is usually too late. The media needs to clarify which aspects have been confirmed by scientific research and which are still unknown, and provide suggestions based on evidence to help people protect themselves and their families.
  From the perspective of human history, the world has never really stopped because of the arrival of the “black swan”. It is conceivable that when the black swan flies away, the sun still rises as usual, and people are more busy than usual. Hegel said: The only lesson people learn from history is that people cannot learn anything from history.

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