Individuals copy the behaviour of others in almost all societies. This is social learning, and it allows new innovations and behaviours to spread. The transmission of behaviour relies on the underlying social network or connections in a group, and individuals are diverse – some with many social connections and others only few. It feels logical that an individual with more social connections will quickly acquire new behaviours, but this assumes that they spread like a contagious disease (known as ‘simple contagion’).
Behavioural spread can be more complex than this, requiring social reinforcement from multiple connections and depending on connections to both informed and uninformed individuals (known as ‘complex contagion’). For example, for risky behaviours like consuming new foods, an individual may only eat the new food after most of its social contacts decided to; here, those with many social connections may develop a behaviour later because it takes longer for its social connections to become ‘informed’.
Researchers from the Department of Biology have explored the relationship between individual social connectivity and behavioural acquisition in a real-world scenario. They created more than 1300 social networks from the foraging associations of over 1700 individually tracked wild great tits (Parus major) over three years. They then simulated different forms of behavioural spread on these real-world networks using four different transmission rules.
The results reveal that where learning depends on the number and strength of informed social connections, higher connectivity – as expected – meant adopting new behaviours faster. However, when the proportion of informed versus uninformed connections was important in learning, this trend was no longer seen. How behaviours spread through real-world social networks has wide-reaching implications across society. Dr Kristina Beck said:
Our results reveal that it might not always be the most social individuals acquiring novel behaviours first, and that less sociable individuals who have fewer connections but occur in tight cliques may be just as important for spreading behaviours.
The researchers also believe the findings could be relevant for those who work with wild populations of animals where changes in behaviour would be beneficial. For example, an endangered population might be at risk due to a risky behaviour, such as consuming a harmful food item. Understanding how behaviours spread are key to at some point proliferating alternative, safer behaviours. While this study used real social networks, behavioural spread was only simulated. Future research could explore the spread of real behaviours in wild animal populations, following different social learning rules.
To read more about this research, published in eLife, visit: https://doi.org/10.7554/eLife.85703
