When to Use It: Dunbar's Number is a concept you might consider when building or managing social networks, communities, or organizations. It's an idea that helps us understand the limitations of our social interactions and relationships.

Think of your social circle as a city filled with people. You are the mayor, and you need to remember each citizen's name, their face, and a little bit about their personal life.

Dunbar's Number suggests that you can effectively manage about 150 citizens. This means that:

1. If your city has 150 or fewer citizens (like a small company or community), you'll probably know everyone fairly well. You'll remember their names, you'll recognize their faces, and you'll know some personal facts about them.

2. However, if your city has hundreds or thousands of citizens (like a large company or online community), it will be much harder to maintain the same level of personal connection with everyone. In this case, you'll likely end up knowing a lot about a few people (your close network), a little about some people (your extended network), and virtually nothing about most people (your distant network).  

 

In summary, Dunbar's Number helps us recognize the cognitive limits of maintaining meaningful social relationships. Understanding this can guide us in designing more effective social structures, from companies and communities to social media platforms. It reminds us that while our networks can scale, the depth and quality of our relationships might not.

Dunbar's Number is considered controversial for several reasons:

1. Methodological concerns: Critics argue that the method used to derive the number, which is based on extrapolating primate social group sizes from neocortex size, is too simplistic. They contend that relying solely on this correlation may not fully account for the complexity of human social relationships and other factors that might influence social group size, such as culture, technology, and socio-economic conditions.

2. Variability in the number: There is a significant range in the estimated value of Dunbar's Number, with some studies suggesting it falls between 100 and 250. This variability raises questions about the validity and generalizability of the concept. It is important to note, however, that Dunbar himself acknowledges the variability and suggests that the number is not a strict limit but rather an approximate value.

3. Evolutionary assumptions: Dunbar's Number is closely tied to the Social Brain Hypothesis, which assumes that the primary driver for the evolution of primate brain size is the complexity of social interactions. Some critics argue that other factors, such as ecological challenges or problem-solving abilities, could have played a more significant role in brain evolution.

4. Applicability to the digital age: With the rise of online social networks, some critics question the relevance of Dunbar's Number in the digital age. They argue that technology might enable people to maintain larger social networks than what the cognitive limit proposed by Dunbar would suggest. However, recent studies have shown that even in online settings, people tend to maintain a similar number of stable relationships, supporting the validity of Dunbar's Number in the digital context (Dunbar, 2016).

Despite these controversies, Dunbar's Number remains an influential concept in the study of social networks and human social behavior. While it may not provide a definitive limit on social group size, it offers valuable insights into the cognitive constraints that shape our social interactions.

Resources

• https://bigthink.com/neuropsych/dunbars-number/
• https://phys.org/news/2021-06-dispute-dunbar-people-relationships.html
• https://www.sciencedaily.com/releases/2021/05/210504211054.htm

Dunbar's Number is an anthropological and psychological concept that posits a cognitive constraint on the number of stable social relationships that humans can effectively maintain. Proposed by British anthropologist Robin Dunbar in the 1990s, this theoretical limit is estimated to be around 150, with variations depending on individual and contextual factors. Dunbar derived this number by examining the correlation between neocortex size and group size in primates, using this relationship to predict human social group size based on the human neocortex size (Dunbar, 1992).

Dunbar's Number is related to several other principles and scientific topics, such as:

1. Social Brain Hypothesis: This hypothesis suggests that the primary driving force behind the evolution of primate brain size, particularly the neocortex, is the complexity of social interactions within their groups (Dunbar, 1998). Dunbar's Number supports this hypothesis, as it demonstrates a link between cognitive capacity and the ability to maintain social relationships.

2. Social Network Analysis: Dunbar's Number has implications for the study of social networks, as it highlights the structural limitations in human social organization. Studies have shown that social networks often display a hierarchical structure with layers or circles of intimacy, corresponding to different cognitive demands (Hill & Dunbar, 2003). This layered structure can help manage relationships within the constraints imposed by Dunbar's Number.

3. Community and Organizational Structure: Dunbar's Number has been applied to the study of communities and organizational structures, such as businesses, religious institutions, and online platforms. Understanding the cognitive limitations on group size can inform the design of more effective and cohesive social structures (Gonçalves, Perra, & Vespignani, 2011).

4. Online Social Networks: Research on the applicability of Dunbar's Number to online social networks has shown that even in the digital realm, people tend to maintain a similar number of stable relationships as they do offline, suggesting that cognitive constraints still apply (Dunbar, 2016).

References

• Dunbar, R. I. M. (1992). Neocortex size as a constraint on group size in primates. Journal of Human Evolution, 22(6), 469-493.
• Dunbar, R. I. M. (1998). The social brain hypothesis. Evolutionary Anthropology: Issues, News, and Reviews, 6(5), 178-190.
• Hill, R. A., & Dunbar, R. I. M. (2003). Social network size in humans. Human Nature, 14(1), 53-72.
• Gonçalves, B., Perra, N., & Vespignani, A. (2011). Modeling users' activity on Twitter networks: Validation of Dunbar's number. PLoS ONE, 6(8), e22656.
• Dunbar, R. I. M. (2016). Do online social media cut through the constraints that limit the size of offline social networks? Royal Society Open Science, 3(1), 150292.