How do bees self-organise? – Orit Peleg in Simplifying Complexity

One of the things that make complexity science so fascinating is the diversity of the systems that it applies to. In this series so far, you’ve learnt about everything from ecologies to economies, tipping points in ecologies and economies, to power and influence in the 1400s, and even the spread of coronavirus in the lungs and the thing that brings all of these different topics together is complexity. This means that we can study one system to help us understand other systems — including bees.

In today’s episode, Orit Peleg, Faculty at the University of Colorado, Boulder, and External Faculty at the Santa Fe Institute, explains how bees self-organise and produce sophisticated behaviour. In this case, you’ll hear how thousands of bees can work out where their queen is at any given point.

Listen at: omny.fm

Homophily-Based Social Group Formation in a Spin Glass Self-Assembly Framework

Jan Korbel, Simon D. Lindner, Tuan Minh Pham, Rudolf Hanel, and Stefan Thurner
Phys. Rev. Lett. 130, 057401

Homophily, the tendency of humans to attract each other when sharing similar features, traits, or opinions, has been identified as one of the main driving forces behind the formation of structured societies. Here we ask to what extent homophily can explain the formation of social groups, particularly their size distribution. We propose a spin-glass-inspired framework of self-assembly, where opinions are represented as multidimensional spins that dynamically self-assemble into groups; individuals within a group tend to share similar opinions (intragroup homophily), and opinions between individuals belonging to different groups tend to be different (intergroup heterophily). We compute the associated nontrivial phase diagram by solving a self-consistency equation for “magnetization” (combined average opinion). Below a critical temperature, there exist two stable phases: one ordered with nonzero magnetization and large clusters, the other disordered with zero magnetization and no clusters. The system exhibits a first-order transition to the disordered phase. We analytically derive the group-size distribution that successfully matches empirical group-size distributions from online communities.

Read the full article at: link.aps.org

RESEARCHER ON THE CLASSIFICATION, ANALYSIS AND MODELLING OF ONLINE DISINFORMATION SPREADING BEHAVIOUR

FBK-CHuB is seeking a Researcher in the field of the classification, analysis and modelling of online disinformation spreading behaviour.
In particular, the candidate will be involved in a large European research project focused on the development of a platform tackling misinformation and disinformation across the EU by empowering scientific researchers and media practitioners with advanced AI-based technologies that: 1) allow multichannel (distinct online social media and news feeds), multilingual and multimodal (textual, visual and audio content) monitoring, detection and recording of misinformation and disinformation on online social media and traditional media; 2) estimate the risk of unreliable information consumption; 3) create a trustworthy online environment involving researchers, media practitioners and policy makers to facilitate the creation and distribution of reliable information and counter-narratives, while labelling and countering mis/disinformation.

Read the full article at: jobs.fbk.eu

The circular economy

A sustainable future requires preservation of the world’s finite resources, which often means the waste from one process loops back and becomes the input for another. Advanced technologies and techniques are helping an array of industries to make reuse and recycling more central to their operations. 

Read the full Outlook at: www.nature.com