Diversity of information and expertise among group members has been identified as a crucial ingredient of collective intelligence. However, many factors tend to reduce the diversity of groups, such as herding, groupthink, and conformity. We show why the individual incentives in financial and prediction markets and the scientific community reduce diversity of information and how these incentives can be changed to improve the accuracy of collective forecasting. Our results, therefore, suggest ways to improve the poor performance of collective forecasting seen in recent political events and how to change career rewards to make scientific research more successful.

 

Optimal incentives for collective intelligence
Richard P. Mann and Dirk Helbing

PNAS

10.1073/pnas.1618722114

Source: www.pnas.org

We collect and analyze the darkweb (a.k.a. the “onionweb”) hyperlink graph. We find properties highly dissimilar to the well-studied world wide web hyperlink graph; for example, our analysis finds that >87% of darkweb sites never link to another site. We compare our results to prior work on world-wide-web and speculate about reasons for their differences. We conclude that in the term “darkweb”, the word “web” is a connectivity misnomer. Instead, it is more accurate to view the darkweb as a set of largely isolated dark silos.

 

Graph Theoretic Properties of the Darkweb
Virgil Griffith, Yang Xu, Carlo Ratti

Source: arxiv.org

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls – both, mobile and landline – and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

 

Grauwin, S. et al. Identifying and modeling the structural discontinuities of human interactions. Sci. Rep. 7, 46677; doi: 10.1038/srep46677 (2017)

Source: www.nature.com