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Register a new userInformation exchange, meaning and redundancy generation in anticipatory systems: self-organization of expectations -- the case of Covid-19
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Inga Ivanova
Publication date
2021
fields
Informatics Engineering
and research's language is
English
Authors
Inga A. Ivanova
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When studying the evolution of complex systems one refers to model representations comprising various descriptive parameters. There is hardly research where system evolution is described on the base of information flows in the system. The paper focuses on the link between the dynamics of information and system evolution. Information, exchanged between different systems parts, before being processed is first provided with meaning by the system. Meanings are generated from the perspective of hindsight, i.e. against the arrow of time. The same information can be differently interpreted by different systems parts (i,e,provided with different meanings) so that the number of options for possible system development is proliferated. Some options eventually turn into observable system states. So that system evolutionary dynamics can be considered as due to information processing within the system. This process is considered here in a model representation. The model under study is Triple Helix (TH) model, which was earlier used to describe interactions between university, industry and government to foster innovations. In TH model the system is comprised of three interacting parts where each part process information ina different way. The model is not limited to the sphere of innovation and can be used in a broader perspective. Here TH is conceptualized in the framework of three compertment model used to describe infectious disease. The paper demonstrates how the dynamics of information and meaning can be incorporated in the description of Covid-19 infectious propagation. The results show correspondence of model predictions with observable infection dynamics.
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Early analyses revealed that dark web marketplaces (DWMs) started offering COVID-19 related products (e.g., masks and COVID-19 tests) as soon as the current pandemic started, when these goods were in shortage in the traditional economy. Here, we broaden the scope and depth of previous investigations by analysing 194 DWMs until July 2021, including the crucial period in which vaccines became available, and by considering the wider impact of the pandemic on DWMs. First, we focus on vaccines. We find 250 listings offering approved vaccines, like Pfizer/BioNTech and AstraZeneca, as well as vendors offering fabricated proofs of vaccination and COVID-19 passports. Second, we consider COVID-19 related products. We reveal that, as the regular economy has become able to satisfy the demand of these goods, DWMs have decreased their offer. Third, we analyse the profile of vendors of COVID-19 related products and vaccines. We find that most of them are specialized in a single type of listings and are willing to ship worldwide. Finally, we consider a broader set of listings simply mentioning COVID-19. Among 10,330 such listings, we show that recreational drugs are the most affected among traditional DWMs product, with COVID-19 mentions steadily increasing since March 2020. We anticipate that our effort is of interest to researchers, practitioners, and law enforcement agencies focused on the study and safeguard of public health.
The COVID-19 pandemic has reshaped the demand for goods and services worldwide. The combination of a public health emergency, economic distress, and misinformation-driven panic have pushed customers and vendors towards the shadow economy. In particular, dark web marketplaces (DWMs), commercial websites accessible via free software, have gained significant popularity. Here, we analyse 851,199 listings extracted from 30 DWMs between January 1, 2020 and November 16, 2020. We identify 788 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds. Finally, we compare trends in their temporal evolution with variations in public attention, as measured by Twitter posts and Wikipedia page visits. We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs, especially now that real vaccines are available and in short supply. We anticipate our analysis will be of interest both to researchers and public agencies focused on the protection of public health.
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