Author: cxdig

The Strength of Absent Ties: Social Integration via Online Dating

We used to marry people to which we were somehow connected to: friends of friends, schoolmates, neighbours. Since we were more connected to people similar to us, we were likely to marry someone from our own race.
However, online dating has changed this pattern: people who meet online tend to be complete strangers. Given that one-third of modern marriages start online, we investigate theoretically, using random graphs and matching theory, the effects of those previously absent ties in the diversity of modern societies.
We find that when a society benefits from previously absent ties, social integration occurs rapidly, even if the number of partners met online is small. Our findings are consistent with the sharp increase in interracial marriages in the U.S. in the last two decades.

 

The Strength of Absent Ties: Social Integration via Online Dating
Josue Ortega, Philipp Hergovich

Source: arxiv.org

Effects of motion in structured populations

In evolutionary processes, population structure has a substantial effect on natural selection. Here, we analyse how motion of individuals affects constant selection in structured populations. Motion is relevant because it leads to changes in the distribution of types as mutations march towards fixation or extinction. We describe motion as the swapping of individuals on graphs, and more generally as the shuffling of individuals between reproductive updates. Beginning with a one-dimensional graph, the cycle, we prove that motion suppresses natural selection for death–birth (DB) updating or for any process that combines birth–death (BD) and DB updating. If the rule is purely BD updating, no change in fixation probability appears in the presence of motion. We further investigate how motion affects evolution on the square lattice and weighted graphs. In the case of weighted graphs, we find that motion can be either an amplifier or a suppressor of natural selection. In some cases, whether it is one or the other can be a function of the relative reproductive rate, indicating that motion is a subtle and complex attribute of evolving populations. As a first step towards understanding less restricted types of motion in evolutionary graph theory, we consider a similar rule on dynamic graphs induced by a spatial flow and find qualitatively similar results, indicating that continuous motion also suppresses natural selection.

 

Effects of motion in structured populations
Madison S. Krieger, Alex McAvoy, Martin A. Nowak
Published 4 October 2017.DOI: 10.1098/rsif.2017.0509

Source: rsif.royalsocietypublishing.org

Temporal Network Epidemiology

This book covers recent developments in epidemic process models and related data on temporally varying networks. It is widely recognized that contact networks are indispensable for describing, understanding, and intervening to stop the spread of infectious diseases in human and animal populations; “network epidemiology” is an umbrella term to describe this research field.

More recently, contact networks have been recognized as being highly dynamic. This observation, also supported by an increasing amount of new data, has led to research on temporal networks, a rapidly growing area. Changes in network structure are often informed by epidemic (or other) dynamics, in which case they are referred to as adaptive networks.

This volume gathers contributions by prominent authors working in temporal and adaptive network epidemiology, a field essential to understanding infectious diseases in real society.

 

Temporal Network Epidemiology
Naoki Masuda, Petter Holme (Eds.)

Source: link.springer.com

The Prize in Economic Sciences 2017

Richard H. Thaler has incorporated psychologically realistic assumptions into analyses of economic decision-making. By exploring the consequences of limited rationality, social preferences, and lack of self-control, he has shown how these human traits systematically affect individual decisions as well as market outcomes.

Limited rationality: Thaler developed the theory of mental accounting, explaining how people simplify financial decision-making by creating separate accounts in their minds, focusing on the narrow impact of each individual decision rather than its overall effect. He also showed how aversion to losses can explain why people value the same item more highly when they own it than when they don’t, a phenomenon called the endowment effect. Thaler was one of the founders of the field of behavioural finance, which studies how cognitive limitations influence financial markets.

Social preferences: Thaler’s theoretical and experimental research on fairness has been influential. He showed how consumers’ fairness concerns may stop firms from raising prices in periods of high demand, but not in times of rising costs. Thaler and his colleagues devised the dictator game, an experimental tool that has been used in numerous studies to measure attitudes to fairness in different groups of people around the world.

Lack of self-control: Thaler has also shed new light on the old observation that New Year’s resolutions can be hard to keep. He showed how to analyse self-control problems using a planner-doer model, which is similar to the frameworks psychologists and neuroscientists now use to describe the internal tension between long-term planning and short-term doing. Succumbing to shortterm temptation is an important reason why our plans to save for old age, or make healthier lifestyle choices, often fail. In his applied work, Thaler demonstrated how nudging – a term he coined – may help people exercise better self-control when saving for a pension, as well in other contexts.

In total, Richard Thaler’s contributions have built a bridge between the economic and psychological analyses of individual decision-making. His empirical findings and theoretical insights have been instrumental in creating the new and rapidly expanding field of behavioural economics, which has had a profound impact on many areas of economic research and policy.

Source: www.nobelprize.org

Where is technology taking the economy?

We are creating an intelligence that is external to humans and housed in the virtual economy. This is bringing us into a new economic era—a distributive one—where different rules apply.

 

Where is technology taking the economy?
By W. Brian Arthur

McKinsey Quaterly

Source: www.mckinsey.com