Axelrod’s Cognitive Networks

Before introducing the cultural diffusion model he is now better known for, Axelrod proposed mapping individuals’ reasoning process as a causal network.

“A person’s beliefs can be regarded as a complex system,” he argued, and, “given a person’s concepts and beliefs, and given certain rules for deducing other beliefs from them” it is therefore possible to model how “a person would make a choice among alternatives” (Axelrod, 1976).

Axelrod called these networks of beliefs and causal relationships “cognitive maps,” and he engaged other scholars in deriving cognitive maps for select political elites using a detailed hand-coding procedure of a subject’s existing documents.

For Axelrod, the representation of beliefs as a network was a natural and obvious extension of how individuals reason. “People do evaluate complex policy alternatives in terms of the consequences of a particular choice would cause, and ultimately of what the sum of these effects would be,” he argued. “Indeed, such cause analysis is built into our language, and it would be very difficult for us to think complete in other terms, even if we tried” (Axelrod, 1976).

Axelrod takes the nodes of these networks to be concepts, with directed edges between them indicating causal links. Importantly, the nodal concepts are not things but rather “variables that can take on different values.” This makes the cognitive map “an algebraic rather than a logical system.”

Axelrod saw great value in the approach of cognitive mapping – seeing them as tools to understand decision-making, resources capable of meaningful policy suggestions, and imagining how individuals’ maps could aggregate into a collective.


Computational Models of Belief Systems & Cultural Systems

Work on belief systems is similar to the research on cultural systems – both use agent-based models to explore how complex systems evolve given a simple set of actor rules and interactions – there are important conceptual differences between the two lines of work.

Research on cultural systems takes a maco-level approach, seeking to explain if, when, and how, distinctive communities of similar traits emerge, while research on belief systems uses comparable methods to understand if, when, and how distinctive individuals come to agree on a given point.

The difference between these approaches is subtle but notable. The cultural systems approach begins with the observation that distinctive cultures do exist, despite local tendencies for convergence, while research on belief systems begins from the observation that groups of people are capable of working together, despite heterogeneous opinions and interests.

In his foundational work on cultural systems, Axelrod begins, “despite tendencies towards convergence, differences between individuals and groups continue to exist in beliefs, attitudes, and behavior” (Axelrod, 1997).

Compare this to how DeGroot begins his exploration of belief systems: “consider a group of individuals who must act together as a team or committee, and suppose that each individual in the group has his own subjective probability distribution for the unknown value of some parameter. A model is presented which describes how the group might reach agreement on a common subjective probability distribution parameter by pooling their individual opinions” (DeGroot, 1974).

In other words, while cultural models seek to explain the presence of homophily and other system-level traits, belief systems more properly seek to capture deliberative exchange. The important methodological difference here is that cultural systems model agent change as function of similarity, while belief systems model agent change as a process of reasoning.



Computational Models of Cultural Systems

Computational approaches to studying the broader social context can be found in work on the emergence and diffusion of communities in cultural system. Spicer makes an anthropological appeal for the study of such systems, arguing that cultural change can only be properly considered in relation to more stable elements of culture. These persistent cultural elements, he argues, can best be understood as ‘identity systems,’ in which individuals bestow meaning to symbols. Spicer notes that there are collective identity systems (i.e., culture) as well as individual systems, and chooses to focus his attention on the former. Spicer talks about these systems in implicitly network terms: identity systems capture “relationships between human beings and their cultural products” (Spicer, 1971). To the extent that individuals share the same relationships with the same cultural products, they are united under a common culture; they are, as Spicer says, “a people.”

Axelrod presents a more robust mathematical model for studying these cultural systems. Similar to Schelling’s dynamic models of segregation, Axelrod imagines individuals interacting through processes of social influence and social selection (Axelrod, 1997). Agents are described with n-length vectors, with each element initialized to a value between 0 and m. The elements of the vector represent cultural dimensions (features), and the value of each element represents an individual’s state along that dimension (traits). Two individuals with the exact same vector are said to share a culture, while, in general, agents are considered culturally similar to the extent to which they hold the same trait for the same feature. Agents on a grid are then allowed to interact: two neighboring agents are selected at random. With a probability equal to their cultural similarity, the agents interact. An interaction consists of selecting a random feature on which the agents differ (if there is one), and updating one agent’s trait on this feature to its neighbor’s trait on that feature. This simple model captures both the process of choice homophily, as agents are more likely to interact with similar agents, and the process of social influence, as interacting agents become more similar over time. Perhaps the most surprising finding of Axelrod’s approach is just how complex this cultural system turns out to be. Despite the model’s simple rules, he finds that it is difficult to predict the ultimate number of stable cultural regions based on the system’s n and m parameters.

This concept of modeling cultural convergence through simple social processes has maintained a foothold in the literature and has been slowly gaining more widespread attention. Bednar and Page take a game theoretic approach, imagining agents who must play multiple cognitively taxing games simultaneously. Their finding that in these scenarios “culturally distinct behavior is likely and in many cases unavoidable” (Bednar & Page, 2007) is notable because classic game-theoretic models fail to explain the emergence of culture at all: rather rational agents simply maximize their utility and move on. In their simultaneous game scenarios, however, cognitively limited agents adopt the strategies that can best be applied across the tasks they face. Cultures, then, emerge as “agents evolve behaviors in strategic environments.” This finding underscores Granovetter’s argument of embeddedness (M. Granovetter, 1985): distinctive cultures emerge because regional contexts influence adaptive choices, which in turn influence an agent’s environment.

Moving beyond Axelrod’s grid implementation, Flache and Macy (Flache & Macy, 2011) consider agent interaction on the small world network proposed by Watts and Strogatz (Watts & Strogatz, 1998). This model randomly rewires a grid with select long-distance ties. Following Granovetter’s strength of weak ties theory (M. S. Granovetter, 1973), the rewired edges in the Watts-Strogatz model should bridge clusters and promote cultural diffusion. Flache and Macy also introduce the notion of the valiance of interaction, considering social influence along dimensions of assimilation and differentiation, and taking social selection to consist of either attraction or xenophobia. In systems with only positively-valenced interaction (assimilation and attraction), they find that the ‘weak’ ties have the expected result: cultural signals diffuse and the system tends towards cultural integration. However, introduction of negatively valenced interactions (differentiation and xenophobia), leads to cultural polarization; resulting in deep disagreement between communities which themselves have high internal consensus.



Having attended a conference last weekend, I meet a lot of people and had a lot of conversations…and had a lot of conversations about meeting new people.

One thing that kept coming up was people’s dislike of utilitarian networking – the idea that, especially when at a conference, you should talk to specific kinds of people or intentionally work on building certain relationships out of a pure utilitarian desire to leverage that relationship for your own good.

Perhaps I simply haven’t attended enough conferences, but I don’t find this concern very…concerning. To be clear, I do find the very idea of utilitarian networking to be distasteful, but I don’t find networking to be inherently utilitarian.

Or perhaps I’m just not doing it right.

In a previously life, I would go to social events and not talk to anyone. Not necessarily out of distaste for networking, but out of a general malaise about life. Then, some how, at some point along the line, I started talking to people.

And what I found was that people are really interesting.

Every conversation is like a window into a whole other universe of personhood. And the less you know the person, the more there is to learn.

So now when I go to events, I talk to people. As many people as meaningfully possible. Not out of a utilitarian drive to advance myself through connection, but out of a genuine desire to meet and learn from other.

Maybe I’m wrong, but I just though that’s what networking is.


Diverse Perspectives and Advertising

In the short half-life of scandals and outrage these days, I know it already seems like forever ago, but I wanted to take a minute to reflect on the “Kendall Jenner Pepsi ad” debacle of 2017. In the ad, reality star/model Jenner “throws off the chains of the modeling industry,” joining a Black Lives Matter protest, and ultimately bringing “everyone together by … handing a cop a Pepsi.”

You can see, perhaps, the problem.

There is plenty to analyze in terms of what is wrong with the ad, but, as someone with a background in marketing, I find myself more interested in a related question: how did the ad get made?

Interestingly, Pepsi used an in-house firm to design the ad – a move which many in agency life fingered as the culprit. If only Pepsi had had an outside perspective, an external agency with a beat on the broader culture, such an ad would never have been made. While there’s no way to know if that may have been a mitigating factor, ad agencies have made their fair share of gaffes, too.

But whether the ad was created by an in-house firm or an outside ad agency, it would have needed to go through numerous iterations and revisions. Numerous people must have looked at the ad concept, script, and footage. And none of them seemingly walked away questioning whether the ad could face backlash.

Now, I don’t know the demographics of the marketers who made this ad, but I’d bet good money that the majority of them were white.

And while that may be an implicit assumption which goes hand in hand with the very notion that this ad was created, it is worth pausing for a moment and reflecting on this.

When company’s make blunders like this, we shouldn’t just mock them and wonder how they got so out of touch. We more or less know, sociologically speaking, exactly how they got out of touch.

When everyone reviewing an ad is more or less the same, we shouldn’t be surprised when they turn out tone-deaf material.

The outrage here shouldn’t just be about one ad or about one company; we should all be outraged that we live in such a deeply segregated society that in a whole room full of people it is hardly surprising that not one black voice was heard.


Defining Deliberation

While there are many definitions of deliberation – and many substantive debates about what constitutes ‘good’ deliberation (or perhaps it must be good to count as deliberation) – I like Jane Mansbridge’s ‘minimalist definition’ as a good starting point for understanding the term.

Deliberation, she writes, is “mutual communication that involves weighing and reflecting on preferences, values and interests regarding matters of common concern.”

While there is much that may be missing from this definition, I do think that it captures the core of what deliberation is all about. It is, fundamentally, a form of communication which engages reason and normative beliefs about shared concerns.

But the simplicity of this definition, perhaps under-states the value of deliberation; the power people can have in shaping their own communities.

Dewey writes that:

Democracy is much broader than a special political form, a method of conducting government, of making laws and carrying on governmental administration by means of popular suffrage and elected officers. It is that, of course. But it is something broader and deeper than that…It is, as we often say, though perhaps without appreciating all that is involved in the saying, a way of life, social and individual. The key-note of democracy as a way of life may be expressed, it seems to me, as the necessity for the participation of every mature human being in formation of the values that regulate the living of men together: which is necessary from the standpoint of both the general social welfare and the full development of human beings as individuals.

When Dewey writes that ‘democracy is a way of life’ he means that the ideal of democracy can only be achieved when we co-create our values and institutions together; when we deliberate to answer the question, what should we do?

But more fundamentally, the Deweyian invocation to democracy as a way of life, tells us that deliberation is democracy. It is not “just talk” or isolated blather. Deliberation is the very stuff of democracy itself – and when we live our lives as good citizens, engaging regularly and rationally in conversation with all members of our community; when we treat every conversation as a chance to improve ourselves and co-create our world; when we take democracy as a way of life –

Then we are indeed creating democracy itself.


The Joint Effects of Content and Style on Debate Outcomes

I am heading out later today to head to the Midwest Political Science Association (MPSA) conference. My advisor, Nick Beauchamp will be presenting our joint work on “The Joint Effects of Content and Style on Debate Outcomes.”

Here is the abstract for that work:

Debate and deliberation play essential roles in politics and government, but most models presume that debates are won mainly via superior style or agenda control. Ideally, however, debates would be won on the merits, as a function of which side has the stronger arguments. We propose a predictive model of debate that estimates the effects of linguistic features and the latent persuasive strengths of different topics, as well as the interactions between the two. Using a dataset of 118 Oxford-style debates, our model’s combination of content (as latent topics) and style (as linguistic features) allows us to predict audience-adjudicated winners with 74% accuracy, significantly outperforming linguistic features alone (66%). Our model finds that winning sides employ stronger arguments, and allows us to identify the linguistic features associated with strong or weak arguments.


Whoa, “Woah”

The interjection “whoa” – defined in the Oxford English Dictionary as: a command to a horse to stop or stand still” or “a general interjection expressing surprise, delight, etc.” has been in use since the early 19th century.

Consider, for example, the use of the word as an intransitive verb in an 1838 issue of New Sporting Magazine: “He..climbed up the fence, ‘whoaing’ and crying to his horse to ‘stand still’.”

There is some evidence that the word has existed since long before that. One etymological dictionary, for example, dates the word to the 1620s; defining it as “a cry to call attention from a distance, a variant of who.”

But in the age of the internet, a funny thing has started happening:

Whoa. W. H. O. A. has more and more frequently come to be spelled as ‘woah’, as if the ‘h’ is precariously trying to escape from the whole messy situation.

In 2013, Slate wrote a whole piece on the gaining popularity of the wrong / new spelling: “All things considered, it’s been a banner year for “whoa,” no matter how you prefer to spell it,” they write.

And, as Mashable points out, the ACLU and Merriam-Webster dictionary recently sorted the whole thing on Twitter:

“We don’t include [woah] as a variant,” Merriam-Webster wrote in response to a query from the ACLU, “but we’re pretty sure you still have the right to say it.”

That is, after all, what it means for English to be a living language.


I Stand With CEU

It is a sad day for democracy and for intellectual freedom. This morning, after an expedited process, Hungary’s Parliament voted 123 yes / 38 against for amendments to the National Higher Education Law that will make it impossible for Central European University (CEU) to operate.

CEU is one of the most prestigious institutions of higher education in central Europe, and a pillar of democracy. Founded after the fall of communism and “based on the premise that human fallibility can be counterbalanced by the critical discussion of ideas and that this critical spirit can be sustained best in societies where citizens have the freedom to scrutinize competing theories and openly evaluate and change government policies.”

The message sent in moving to shutter this great institution is clear. As MEP Tamás Meszerics – who was denied the opportunity to address assembly in opposition of the measure – wrote in his statement: the government hates everything it cannot control.

Hungarian Prime Minster, Viktor Orbán has long been a leading symbol of Europe’s rising radical right. The election of President Trump, I’m afraid, has only emboldened his efforts against democratic values.

The attack against CEU is a tragic move against a valuable institution, and raises disturbing implications for intellectual freedom and democracy around the world. We cannot allow leaders of any part to silence critical voices, legislate against reason, and stifle political dissent.

To be clear, the fight for CEU is far from over. In Budapest today, thousands took to the street to protest this outrageous legislation. CEU – which just days ago found itself fighting for its life – has a helpful guide of actions you can take to support the institution. Specifically, they encourage you to:

I stand with CEU – do you?


Public Opinion and Social Influence

The presence of homophily is frequently found as a core feature of social networks. The principle that “similarity breeds connection” results in personal networks skewed towards homogeneity along numerous demographic and interpersonal lines (McPherson, Smith-Lovin, & Cook, 2001).

Festinger argues that homophily is a direct result of social influence: beliefs are only coherent through a process of social comparison and therefore people “tend to move into groups which, in their own judgment, hold opinions which agree with their own” (Festinger, 1954). The problem of embeddedness  – that people’s attempts at purposive action are embedded in concrete, ongoing systems of social relations – is inherent in this argument.

Reviewing the literature on social comparison, Festinger finds that individuals’ beliefs are malleable to social influence because the beliefs of others serve as guideposts in forming one’s own opinion. Foreshadowing Sunstein’s ‘law of group polarization’ (Sunstein, 1999), Festinger argues that this process of forming beliefs through social comparison is a primary driver of what he calls “social quiescence” (Festinger, 1954). This in turn serves as a driver for homophily, as people self-select out of groups unable to reach social quiescence, instead selecting into groups that more appropriately “satisfy their drive for self evaluation.”

Within the political domain, Lazarsfeld pioneered an understanding of public opinion as a process of social influence: a process driven significantly by personal conversations and everyday talk. While earlier understandings took media to be the primary source of political information and influence (Lippmann, 1922), Lazarsfeld suggests a “two-step flow” of communication: ideas and opinions may originate in media, but they flow first to opinion leaders.

What we call public opinion is then formed in a second step when these leaders disseminate information along lines of social influence. Importantly, opinion leaders generally exert greater social power than media, due to the many “psychological advantages” personal contacts have in exerting political influence (Lazarsfeld, Berelson, & Gaudet, 1948). These advantages include trust, conflict avoidance, and “persuasion without conviction,” e.g., the ability to actually take someone to the polls.

Perhaps most interesting for deliberative theory, however, is Lazarsfeld’s argument that “the weight of personal contacts upon opinion lies, paradoxically, in their greater casualness and non-purposiveness in political matters” (Lazarsfeld et al., 1948). In purposive political talk, individuals engage critically and intentionally, mentally prepared with “armor against influence.” Everyday talk, on the hand, catches us unprepared.

The passive exposure that comes from casual conversations presents a pervasive opportunity for powerful personal influence. We again see this argument manifest in Mutz and Mondak’s study of the workplace as a site for cross-cutting political dialogue. Workplaces may have a smaller proportion of political conversations than other settings, but the sheer volume of casual conversations makes workplaces as a key setting for political contact (Mutz, 2002).

Such public-minded talk ceased to be the sole purview of the Greek agorá long ago: when democracy is a way of living, as Dewey writes, even the most seemingly mundane sites of human interaction become critical elements of the deliberative system.