Blaine A. White, “The Argument,” 2017

Read the Reflection, written 25 August 2021, below the following original Transmission.

The oldest and strongest emotion of mankind is fear, and the oldest and strongest kind of fear is fear of the unknown.” — H.P. Lovecraft

Our global crisis has produced a variety of personal and larger social responses, from social unrest to widespread fear. My colleague Juan Pablo Cardenas (Net-Works, Chile) and I have been studying the spread of fear and social unrest by analyzing social media in crisis contexts, particularly around the COVID-19 pandemic.

Our research examines the correlation of crisis-related behaviors with geographic isolation, group size, and other factors. This should give us an idea of the characteristics, perhaps universal, that occur in these types of tumultuous events — whether massive shifts in employment from one sector to another or political protests in response to a government’s handling of a pandemic.

Few concepts have such diverse connotations as crisis. Current approaches that help to define the concept — from different fields such as epistemology and the social sciences — tend to deal with its negative connotations. Putting less emphasis on value and greater emphasis on quantification can contribute to a more general understanding of the phenomenon.

Our working hypothesis is that crises are manifestations of dynamics in all adaptive systems linked to the constant and spontaneous increase of the system’s complexity or internal information. We approach these concepts rigorously using large datasets and network science.

Based on the analysis of a large social dataset of communication events on Twitter, our analysis demonstrates that periods of greatest activity (a fully developed crisis) coincide with an increase in the number of nodes in a network of conversations as well as an increase in the number of components (maximal connected sub-graphs). Non-technically, this means that there are significantly more conversations and that these become increasingly structured around a common set of themes. 

A crisis is therefore characterized on the one hand by a combination of more intense and more concentrated activity. On the other hand, tweets (in the case of social media data) during a fully developed crisis tend to be addressed to specific users — whereas in periods of low crisis, tweets tend to involve messages of lower specificity and greater reach (i.e., opinions are less binding).

These are just a couple of ways in which we can explore quantitative network properties that reveal features of crisis behavior, and that in some cases could provide early warning signs of an impending crisis. In a couple of our studies, Social Crises: Signatures of Complexity in a Fast-Growing Economy and Social Crises: A Network Model Approach, we found early warning signs more than a year in advance of the deep social crisis in Chile that began in October 2019.

With respect to early warning signs, we have been very interested in the larger question of how an ongoing social crisis like the one in Chile relates to the crisis of Covid-19. Another set of deep questions relates to how history influences outcomes. In a dynamic system, this is called hysteresis; we are only now exploring how history modifies future behavior.

To pull together relevant research on these outstanding questions, I launched a Research Topic in the open-access journal Frontiers, dedicated to “Social Crisis.” All are welcome to take a look and see if it has any value to them.

The deadline for abstracts is August 12, 2020, with manuscripts due by December 12, 2020. By sharing research and information, we can begin to answer the many questions that remain in relation to how fear and social unrest interact across social media, and how to find the signal in all the noise.

Miguel Fuentes
Santa Fe Institute

T-006 (Fuentes) PDF

Read more posts in the Transmission series, dedicated to sharing SFI insights on the coronavirus pandemic.

Listen to SFI President David Krakauer discuss this Transmission in episode 27 of our Complexity Podcast.


August 25, 2021

COVID-19, a Particle Accelerator

Despite the fact that COVID-19 irrupted in every country and became an unquestioned and fundamental issue of global importance, the unknown aspects of this pandemic—its direct and indirect consequences—continue to emerge.

My lab’s preliminary work on social crises presented in Transmission T-006 suggested possible slowed-down dynamics; government-imposed total or partial lockdowns (what is known as dynamic quarantines) would lead to strong blockages in social mobility. Despite the fact that the mobility restrictions hindered big demonstrations and street riots—events that put great pressure on the status quo—information continues flowing freely on different digital platforms. Thus, in Chile, where we have installed our virtual laboratory and case study, and in other places, COVID-19 has become a true particle accelerator; it has been one of the important actors accelerating the processes that lead to deep social changes.

In general, the intrinsic adaptive nature of a social system allows it to overcome not only the challenges imposed by the environment and external forces acting on it, but also its internal pressures. This adaptive process is arguably associated with an increase in complexity, which we can observe in a variety of innovative social artifacts, greater diversity of the system’s components, and new forms of organization, among other transformations. However, the dynamical adaptations of social systems have a cost and must be managed; otherwise, they can trigger social unrest and deep crisis processes. Further, the emergence of the internet and other information technologies has accelerated and magnified the process of adaptation of social systems. These technologies have broken down geographical barriers, strengthened globalization, and significantly increased both social interaction and the flow of information. Although social crises have accompanied humanity since its origins, they have increased in magnitude and frequency in recent decades. These contemporary social crises could have their origin in the emergence of the so-called “Networked Society.” That is why online social networks have become a kind of projection of those traditional face-to-face human relationships and interactions, sharing signs and developing their own particularities, assuming an unusual role in the development, and even in the genesis, of some of these social-crisis events. 1

We strongly believe that it is not enough to think about the virtues of “self-organization” in the social system at all scales, since in principle the speed of change and adaptation have very different timescales. In principle, this lack of governmental investment in a complexity and big-picture perspective has led to the emergence of an increasing number of social outbreaks around the globe in recent years.

In our recent work “The Structure of Online Information behind Social Crises,” published in Frontiers in Physics, we explore the close relationship between adaptation, complexity, and crisis, showing the particular ways that complexity is expressed in a digital social environment.

As expected, we observe the polarization of the society and the negative sentiment of messages in times of crisis. However, our results also show that, during times of crisis, social organizations experience a loss of order. As a result, new complex and ephemeral information structures emerge, seemingly early warning signs of profound social transformations. In contrast to classical early warnings that reach a bifurcation or critical point, these early warnings are signals mounted on some underlying information with a lot of fluctuation and noise—they are signals within the crisis. COVID-19 has accelerated the appearance of these signals and the transformation processes of the system, a product of increased unemployment, health crisis, mobility, psychological impacts on society at all ages, etc.

From the analytical point of view, it has been necessary to investigate new territories. Researchers have built new metrics to understand the particularities of digital systems in times of crisis and to learn from their subtle signals. In our case we have been able to create tools that clearly indicate possible threshold states in the social systems. We now have more information to propose plausible explanations, and thus increase the understanding of these complex systems. Even so, it would be an exaggeration to say that we fully or mostly understand the system. Returning to the beginning of this article, the consequences of COVID-19 have not fully unfolded. We have new data, intuitions, and predictive tools, but complete understanding, as always in science, is still open.

Read more thoughts on the COVID-19 pandemic from complex-systems researchers in The Complex Alternative, published by SFI Press.

Reflection Footnotes

 1 These concepts were first laid out in J.P. Cárdenas, G. Olivares, et al., 2021, “The Structure of Online Information behind Social Crises,” Frontiers in Physics 9: 650648, doi: 10.3389/fphy.2021.650648.