The worrisome likelihood that Russians and other malevolent actors are tinkering with public opinion in Western Europe and the United States through social media creates various kinds of anxiety. Are our democratic values so fragile that a few thousand Facebook or Twitter memes could put us on a different plane about important questions like anti-Muslim bigotry, racism, intolerance, or fanaticism about guns? Can a butterfly in Minsk create a thunderstorm of racism in Cincinnati? Have white supremacy and British ultra-nationalism gone viral?
There is an interesting analogy here with the weather. The weather next Wednesday is the net consequence of a number of processes and variables, none of which are enormously difficult to analyze. But in their complex interactions they create outcomes that are all but impossible to forecast over a period of more than three days. And this suggests the interesting idea that perhaps public opinion is itself the result of complex and chaotic processes that give rise to striking forms of non-linear change over time.
Can we do a better job of understanding the dynamics of public opinion by making use of the tools of complexity theory? Here is a summary description of complex systems provided by John Holland in Complexity: A Very Short Introduction:
Complexity, once an ordinary noun describing objects with many interconnected parts, now designates a scientific field with many branches. A tropical rainforest provides a prime example of a complex system. The rainforest contains an almost endless variety of species—one can walk a hundred paces without seeing the same species of tree twice, and a single tree may host over a thousand distinct species of insects. The interactions between these species range from extreme generalists (‘ army’ ants will consume most anything living in their path) to extreme specialists (Darwin’s ‘comet orchid’, with a foot-long nectar tube, can only be pollinated by a particular moth with a foot-long proboscis—neither would survive without the other). Adaptation in rainforests is an ongoing, relatively rapid process, continually yielding new interactions and new species (orchids, closely studied by Darwin, are the world’s most rapidly evolving plant form). This lush, persistent variety is almost paradoxical because tropical rainforests develop on the poorest of soils—the rains quickly leach all nutrients into the nearest creek. What makes such variety possible? (1)
Let’s consider briefly how public opinion might fit into the framework of complexity theory. On the positive side, public opinion has some of the dynamic characteristics of systems that are often treated as being complex: non-linearity, inflection points, critical mass. Like a disease, a feature of public opinion can suddenly “go viral” — reproduce many times more rapidly than in previous periods. And the collective phenomenon of public opinion has a feature of “self-causation” that finds parallels in other kinds of systems — a sudden increase in the currency of a certain attitude or belief can itself accelerate the proliferation of the belief more broadly.
On the negative side, the causal inputs to public opinion dynamics do not appear to be particularly “complex” — word-of-mouth, traditional media, local influencers, and the new factor of social media networks like Twitter, Weibo, or Facebook. We might conceptualize a given individual’s opinion formation as the net result of information and influence received through these different kinds of inputs, along with some kind of internal cognitive processing. And the population’s “opinions” are no more than the sum of the opinions of the various individuals.
Most fundamentally — what are the “system” characteristics that are relevant to the dynamics of public opinion in a modern society? How does public opinion derive from a system of individuals and communication pathways?
This isn’t a particularly esoteric question. We can define public opinion at the statistical aggregate of the distribution of beliefs and attitudes throughout a population — recognizing that there is a distribution of opinion around every topic. For example, at present public opinion in the United States on the topic of President Trump is fairly negative, with a record low 35% approval rating. And the Pew Research Center finds that US public opinion sees racism as an increasingly important problem (link):
Complexity theorists like Scott Page and John Holland focus much attention on a particular subset of complex systems, complex adaptive systems (CAS). These are systems in which the agents are themselves subject to change. And significantly, public opinion in a population of human agents is precisely such a system. The agents change their opinions and attitudes as a result of interaction with other agents through the kinds of mechanisms mentioned here. If we were to model public opinion as a “pandemonium” process, then the possibility of abrupt non-linearities in a population becomes apparent. Assume a belief-transmission process in which individuals transmit beliefs to others with a volume proportional to their own adherence to the belief and the volume and number of other agents from whom they have heard the belief, and individuals adopt a belief in proportion to the number and volume of voices they hear that are espousing the belief. Contagion is no longer a linear relationship (exposure to an infected individual results in X probability of infection), but rather a non-linear process in which the previous cycle’s increase leads to amplified infection rate in the next round.
Here is a good review article of the idea of a complex system and complexity science by Ladyman, Lambert and Wiesner (link, link). Here is a careful study of the diffusion of “fake news” by bots on Twitter (link, link). (The graphic at the top is taken from this article.) And here is a Ph.D. dissertation on modeling public opinion by Emily Cody (link).