Anthropologists have long argued that fear of victimization through witchcraft accusations promotes cooperation in small-scale societies. Others have argued that witchcraft beliefs undermine trust and therefore reduce social cohesion. However, there are very few, if any, quantified empirical examples demonstrating how witchcraft labels can structure cooperation in real human communities. Here we show a case from a farming community in China where people labelled zhu were thought capable of supernatural activity, particularly poisoning food. The label was usually applied to adult women heads of household and often inherited down the female line. We found that those in zhuhouseholds were less likely to give or receive gifts or farm help to or from non-zhu households; nor did they have sexual partnerships or children with those in non-zhu households. However, those in zhuhouseholds did preferentially help and reproduce with each other. Although the tag is common knowledge to other villagers and used in cooperative and reproductive partner choice, we found no evidence that this assortment was based on cooperativeness or quality. We favour the explanation that stigmatization originally arose as a mechanism to harm female competitors. Once established, fear that the trait is transmissible may help explain the persistence of this deep-rooted cultural belief.

Source: Nature

Recently Aaron Clauset and his colleague share their new study: “Scale-free networks are rare”. In this study, they found scale-free network structure is not so prevalent based on their statistical analyses of almost 1000 network datasets across different domains. In particular, their results indicate only 4% of the datasets showing the strongest-possible evidence of scale-free structure and 52% demonstrating the weakest-possible evidence.

Additionally, this study has invoked intense conversations over Twitter. For instance, Laszlo Barabasi retweeted Aaron Caluset’s tweet, saying “Every 5 years someone is shocked to re-discover that a pure power law does not fit many networks. True: Real networks have predictable deviations. Hence forcing a pure power law on these is like…fitting a sphere to the cow. Sooner or later the hoof will stick out.”

Link to the paper: https://arxiv.org/abs/1801.03400

Link to Barabasi’s retweet: https://twitter.com/barabasi/status/952920675592953856

Recently, Omodei, Brashears, and Arenas published a paper about describing a mechanistic model of human network recall and demonstrate its sufficiency for capturing human recall behavior based on experimental data. They found that human recall is based on accurate recall of a hub of high degree actors and also uses compression heuristics (i.e., schemata simplifying the encoding and recall of social information) for both structural and affective information.

The original paper is here: https://www.nature.com/articles/s41598-017-17385-z