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An analysis of all Wikimedia projects shows that a small number of editors have a disproportionately large influence in the formation of collective knowledge.
Bollen et al. tracked changes in the emotions of Twitter users before and after they expressed a feeling online. Emotions grow quickly before—and decrease rapidly after—their expression, confirming previous affect labeling studies showing that putting one’s feelings into words can alleviate their intensity.
The attention received by cultural products—including scientific papers, patents, songs, movies and biographies—decays following a biexponential function, suggesting that collective memory follows a universal pattern.
McGovern and co-workers combine human brain signal measurements underlying decision formation with computational modelling to probe age-related differences in perceptual decision-making.
Smithers et al. find that, although there is some evidence that non-cognitive skills are associated with improved academic, psychosocial and health outcomes, the evidence is weak and heterogeneous. More rigorous research is required in this field.
Using a high-throughput experimental design and statistical modelling, the authors show how jurors and lawyers weigh different types of crime and evidence when assessing the guilt of someone accused of a crime.
Jepma and colleagues provide evidence that prior beliefs about pain influence perceived intensity of pain, and the degree of learning about pain intensity. This finding helps to explain why beliefs are often resistant to updating with experience.
A seven-week school-based field experiment shows that social-rewards schemes increase physical activity in preadolescents, with girls being more receptive to reciprocal and boys to team rewarding schemes.
As children grow, so does their knowledge of language. Sizemore et al. describe knowledge gaps, manifesting as topological cavities, in toddlers’ growing semantic network. These gaps progress similarly, independent of the order in which children learn words.
The N400 evoked potential is a window to meaning in the brain, but it remains incompletely understood. The authors provide a unified explanation of the N400 in a neural network model that avoids the commitments of traditional approaches to meaning in language.
Rutherford et al. analyse temporal, network and hierarchical effects to uncover, understand and quantify competing mechanisms of constitutional change worldwide.
Nowak and colleagues present a game theoretic model that explains how behaviours like subtlety, modesty and anonymous good deeds can be maintained under the standard model of reputation building and indirect reciprocity.
Analytis et al. study social learning strategies for matters of taste and test their performance on a large-scale dataset. They show why a strategy’s success depends both on people’s level of experience and how their tastes relate to those of others.
Lindström and Tobler find that ostracism of individuals can emerge incidentally, based on initial group structure, and is propagated by a simple reinforcement learning mechanism. The same mechanism can be used to reduce incidental ostracism.
High arousal enables young people to better detect salient stimuli. In older people, arousal leads to increased processing of all stimuli. This difference can be explained by age-related changes in how the locus coeruleus–noradrenaline system interacts with cortical attention networks.
In a common-pool resource experiment, Koomen and Herrmann show that six-year-old children are collectively able to avoid collapsing a shared resource and use similar strategies to adults.
A model of minority–majority group interactions shows that minority cultural practices can be preserved from cultural homogenization where a group boundary allows free movement of minority members, but excludes members of the more powerful majority.
Using an imagery-perception paradigm, the authors find that imagined speech affects the perceived loudness of sound. They also show that early neural responses correlate with the loudness ratings, even without external stimulation.
Glaze et al. show that individual variability in learning from noisy evidence involves a bias–variance trade-off that is best explained by a model using a sampling algorithm that approximates optimal inference.
Waniek and colleagues show that individuals and communities can disguise themselves from detection online by standard social network analysis tools through simple changes to their social network connections.