Conformity to the descriptive norms of people with opposing political or social beliefs

Epistemic Communities under Active Inference

The spread of ideas is a fundamental concern of today’s news ecology. Understanding the dynamics of the spread of information and its co-option by interested parties is of critical importance. Research on this topic has shown that individuals tend to cluster in echo-chambers and are driven by confirmation bias. In this paper, we leverage the active inference framework to provide an in silico model of confirmation bias and its effect on echo-chamber formation. We build a model based on active inference, where agents tend to sample information in order to justify their own view of reality, which eventually leads to them to have a high degree of certainty about their own beliefs. We show that, once agents have reached a certain level of certainty about their beliefs, it becomes very difficult to get them to change their views. This system of self-confirming beliefs is upheld and reinforced by the evolving relationship between an agent’s beliefs and observations, which over time will continue to provide evidence for their ingrained ideas about the world. The epistemic communities that are consolidated by these shared beliefs, in turn, tend to produce perceptions of reality that reinforce those shared beliefs. We provide an active inference account of this community formation mechanism. We postulate that agents are driven by the epistemic value that they obtain from sampling or observing the behaviours of other agents. Inspired by digital social networks like Twitter, we build a generative model in which agents generate observable social claims or posts (e.g., ‘tweets’) while reading the socially observable claims of other agents that lend support to one of two mutually exclusive abstract topics. Agents can choose which other agent they pay attention to at each timestep, and crucially who they attend to and what they choose to read influences their beliefs about the world. Agents also assess their local network’s perspective, influencing which kinds of posts they expect to see other agents making. The model was built and simulated using the freely available Python package pymdp. The proposed active inference model can reproduce the formation of echo-chambers over social networks, and gives us insight into the cognitive processes that lead to this phenomenon.

Different drives of herding: An exploratory study of motivations underlying social conformity

We often align our behaviors, attitudes, and opinions in line with a majority of others, a phenomenon known as "social conformity." A seminal framework has proposed that conformity behaviors are mainly driven by three fundamental motives: a desire to gain more information to be accurate, to obtain social approval from others, and to maintain a favorable self-concept. However, previous studies usually have interpreted conformity behaviors as driven by one motive or another, largely ignoring the fact that human behaviors could be concurrently induced by multiple and even conflicting motivations. Adopting a typical conformity paradigm widely used in previous studies, we explored distinct and concurrent motives underlying the same conformity behavior, combining personality and individual differences with more nuanced analyses of observed conformity behaviors. Our findings provide novel evidence to show that three motivations exist within a single conformity behavior, suggesting that multiple motivations drive the conformity concurrently. These findings provide a potential solution for the extensive debate about what drives human social conformity and help to better understand the conformity behavior in daily life.

COVID-19 vaccine delay: An examination of United States residents' intention to delay vaccine uptake

The current study examines differences between COVID-19 vaccine intention and delay. A survey was administered to 585 US respondents in late November 2020 as part of an online longitudinal study. Respondents provided information on whether they would obtain a COVID-19 vaccine, once available, and how long they intended to wait before obtaining it. In the negative intention group, 3.4% reported waiting a few weeks, 34.0% waiting a few months, and 62.6% never getting vaccinated. In multivariable models, social norms were a significant and independent predictor of all vaccine delay and intention models. Vaccine delay was associated with low levels of worry about becoming infected with COVID-19, political conservatism, concerns about vaccine side effects, and low levels of believing a vaccine would be effective. Negative vaccine intentions were associated with worries about becoming infected with COVID-19, concerns about vaccine side effects, beliefs that the vaccines were developed too quickly, and low endorsement of the altruistic belief that older people should have vaccination priority. The study results highlight the importance of a multifactorial approach to assessing vaccine attitudes. The findings suggest that uptake programs should focus on enhancing pro-vaccine norms.

Does Salience of Neighbor-Comparison Information Attract Attention and Conserve Energy? Eye-Tracking Experiment and Interview with Korean Local Apartment Residents

The purpose of this paper is to examine whether salience of neighbor comparison information attracts more attention from residents and consequently leads to significant energy conservation. An eye-tracking experiment on 54 residents in a local apartment complex in Korea found that the average time of attention to the neighbor comparison information increased to 277 ms when the size of the information was four times larger and the information was located to the far left. However, the interviews with the subjects suggest that salience of the information is seemingly unrelated to energy conservation, because most of them did not agree with the social consensus that individuals need to refrain from consuming energy when they know that they have consumed more than the neighbor’s average. Utility data on 502 households in the apartments revealed that, of the households notified that they consumed more than their neighbors, only less than 50% reduced their energy consumption, which supports the interview results. Therefore, it was concluded that neighbor comparison information did not lead to significant energy conservation effects in the community, although salience of the information contributed to attracting more attention to the information. Unavailable household data remained as limitation to clarify the effect by households.

How (many) descriptive claims about political polarization exacerbate polarization

Recently, researchers and reporters have made a wide range of claims about the distribution, nature, and societal impact of political polarization. Here I offer reasons to believe that even when they are correct and prima facie merely descriptive, many of these claims have the highly negative side effect of increasing political polarization. This is because of the interplay of two factors that have so far been neglected in the work on political polarization, namely that (1) people tend to conform to descriptive norms (i.e., norms capturing [perceptions of] what others commonly do, think, or feel), and that (2) claims about political polarization often convey such norms. Many of these claims thus incline people to behave, cognize, and be affectively disposed in ways that contribute to social division. But there is a silver lining. People’s tendency to conform to descriptive norms also provides the basis for developing new, experimentally testable strategies for counteracting political polarization. I outline three.