Category Archives: epistemic networks

People are not Points in Space

Newly published: Levine, P. (2024). People are not Points in Space: Network Models of Beliefs and Discussions. Critical Review, 1–27 (2024). https://doi.org/10.1080/08913811.2024.2344994 (Or a free pre-print version)

Abstract:

Metaphors of positions, spectrums, perspectives, viewpoints, and polarization reflect the same model, which treats beliefs—and the people who hold them—as points in space. This model is deeply rooted in quantitative research methods and influential traditions of Continental philosophy, and it is evident in some qualitative research. It can suggest that deliberation is difficult and rare because many people are located far apart ideologically, and their respective positions can be explained as dependent variables of factors like personality, partisanship, and demographics. An alternative model treats a given person’s beliefs as connected by reasons to form networks. People disclose the connections among their respective beliefs when they discuss issues. This model offers insights about specific cases, such as discussions conducted on two US college campuses, which are represented here as belief-networks. The model also supports a more optimistic view of the public’s capacity to deliberate.

An Association as a Belief Network and Social Network

This is a paper that I presented at the Midwest Political Science Association on April 6, 2024. I hope to reproduce this study with another organization before publishing the results as a comparison. I am open to investigating groups that you may be involved with–a Rotary Club like the one in this study, a religious congregation, or something else. Please contact me if you are interested in exploring such a study.

Abstract

A social network is composed of individuals who may have various relationships with one another. Each member of such a network may hold relevant beliefs and may connect each belief to other beliefs. A connection between two beliefs is a reason. Each member’s beliefs and reasons form a more-or-less connected network. As members of a group interact, they share some of their respective beliefs and reasons with peers and form a belief-network that represents their common view. However, either the social network or the belief network can be disconnected if the group is divided.

This study mapped both the social network and the belief-network of a Rotary Club in the US Midwest. The Club’s leadership found the results useful for diagnostic and planning purposes. This study also piloted a methodology that may be useful for social scientists who analyze organizations and associations of various kinds.

Beliefs and connections among beliefs in a club

An Association as a Belief Network and Social Network

I will present a paper entitled “An Association as a Belief Network and Social Network” at next week’s Midwestern Political Science Association meeting (remotely). This is the paper.

Abstract:

A social network is composed of individuals who may have various relationships with one another. Each member of such a network may hold relevant beliefs and may connect each belief to other beliefs. A connection between two beliefs is a reason. Each member’s beliefs and reasons form a more-or-less connected network. As members of a group interact, they share some of their respective beliefs and reasons with peers and form a belief-network that represents their common view. However, either the social network or the belief network can be disconnected if the group is divided.

This study mapped both the social network and the belief-network of a Rotary Club in the US Midwest. The Club’s leadership found the results useful for diagnostic and planning purposes. This study also piloted a methodology that may be useful for social scientists who analyze organizations and associations of various kinds.

Two illustrative graphs …

Below is the social network of the organization. A link indicates that someone named another person as a significant influence. The size of each dot reflects the number of people who named that individual. The network is connected, not balkanized. However, there are definitely some insiders, who have lots of connections, and a periphery.

The belief-network is shown above this post. The nodes are beliefs held by members of the group. A link indicates that some members connect one belief to another as a reason, e.g., “I appreciate friendships in the club” and therefore, “I enjoy the meetings” (or vice-versa). Nodes with more connections are larger and placed nearer the center.

One takeaway is that members disagree about certain matters, such as the state of the local economy, but those contested beliefs do not serve as reasons for other beliefs, which prevents the group from fragmenting.

I would be interested in replicating this method with other organizations. I can share practical takeaways with a group while learning more from the additional case.

See also: a method for analyzing organizations

people are not points in space

This is the video of a lecture that I gave at the Institute H21 symposium in Prague last September. The symposium was entitled Democracy in the 21st Century: Challenges for an Open Society, and my talk was: “People Are Not Points in Space: Opinions and Discussions as Networks of Ideas.” I’m grateful for the opportunity to present and for the ideas of other participants and organizers.

My main point was that academic research currently disparages the reasoning potential of ordinary people, and this skepticism discourages efforts to protect and enhance democratic institutions. I think the low estimate of people’s capacity is a bias that is reinforced by prevalent statistical methods, and I endorse an alternative methodology.

See also:  individuals in cultures: the concept of an idiodictuon; Analyzing Political Opinions and Discussions as Networks of Ideas; a method for analyzing organizations

can AI help governments and corporations identify political opponents?

In “Large Language Model Soft Ideologization via AI-Self-Consciousness,” Xiaotian Zhou, Qian Wang, Xiaofeng Wang, Haixu Tang, and Xiaozhong Liu use ChatGPT to identify the signature of “three distinct and influential ideologies: “’Trumplism’ (entwined with US politics), ‘BLM (Black Lives Matter)’ (a prominent social movement), and ‘China-US harmonious co-existence is of great significance’ (propaganda from the Chinese Communist Party).” They unpack each of these ideologies as a connected network of thousands of specific topics, each one having a positive or negative valence. For instance, someone who endorses the Chinese government’s line may mention US-China relationships and the Nixon-Mao summit as a pair of linked positive ideas.

The authors raise the concern that this method would be a cheap way to predict the ideological leanings of millions of individuals, whether or not they choose to express their core ideas. A government or company that wanted to keep an eye on potential opponents wouldn’t have to search social media for explicit references to their issues of concern. It could infer an oppositional stance from the pattern of topics that the individuals choose to mention.

I saw this article because the authors cite my piece, “Mapping ideologies as networks of ideas,” Journal of Political Ideologies (2022): 1-28. (Google Scholar notified me of the reference.) Along with many others, I am developing methods for analyzing people’s political views as belief-networks.

I have a benign motivation: I take seriously how people explicitly articulate and connect their own ideas and seek to reveal the highly heterogeneous ways that we reason. I am critical of methods that reduce people’s views to widely shared, unconscious psychological factors.

However, I can see that a similar method could be exploited to identify individuals as targets for surveillance and discrimination. Whereas I am interested in the whole of an individual’s stated belief-network, a powerful government or company might use the same data to infer whether a person would endorse an idea that it finds threatening, such as support for unions or affinity for a foreign country. If the individual chose to keep that particular idea private, the company or government could still infer it and take punitive action.

I’m pretty confident that my technical acumen is so limited that I will never contribute to effective monitoring. If I have anything to contribute, it’s in the domain of political theory. But this is something–yet another thing–to worry about.

See also: Mapping Ideologies as Networks of Ideas (talk); Mapping Ideologies as Networks of Ideas (paper); what if people’s political opinions are very heterogeneous?; how intuitions relate to reasons: a social approach; the difference between human and artificial intelligence: relationships