Using open source data, we observe the fascinating dynamics of nighttime light. Following a global economic regime shift, the planetary center of light can be seen moving eastwards at a pace of about 60 km per year. Introducing spatial light Gini coefficients, we find a universal pattern of human settlements across different countries and see a global centralization of light. Observing 160 different countries we document the expansion of developing countries, the growth of new agglomerations, the regression in countries suffering from demographic decline and the success of light pollution abatement programs in western countries.
Study the way people make mobile phone calls in metropolitan areas and you can see a city breathe, say computer scientists.
The results reveal some fascinating patterns in city structure. For a start, every city undergoes a kind of respiration in which people converge into the center and then withdraw on a daily basis, almost like breathing. And this happens in all cities. This “suggests the existence of a single ‘urban rhythm’ common to all cities,” say Louail and co.
The idea that social media sites such as Twitter can predict the future has a controversial history. In the last few years, various groups have claimed to be able to predict everything from the outcome of elections to the box office takings for new movies.
It’s fair to say that these claims have generated their fair share of criticism. So it’s interesting to see a new claim come to light.
Today, Nathan Kallus at the Massachusetts Institute of Technology in Cambridge says he has developed a way to predict crowd behaviour using statements made on Twitter. In particular, he has analysed the tweets associated with the 2013 coup d’état in Egypt and says that the civil unrest associated with this event was clearly predictable days in advance.
Why does a mouse's heart beat about the same number of times in its lifetime as an elephant's, although the mouse lives about a year, while an elephant sees 70 winters come and go? Why do small plants and animals mature faster than large ones? Why has nature chosen such radically different forms as the loose-limbed beauty of a flowering tree and the fearful symmetry of a tiger?
These questions have puzzled life scientists since ancient times. Now an interdisciplinary team of researchers from the University of Maryland and the University of Padua in Italy propose a thought-provoking answer based on a famous mathematical formula that has been accepted as true for generations, but never fully understood. In a paper published the week of Feb. 17, 2014 in the Proceedings of the National Academy of Sciences, the team offers a re-thinking of the formula known as Kleiber's Law. Seeing this formula as a mathematical expression of an evolutionary fact, the team suggests that plants' and animals' widely different forms evolved in parallel, as ideal ways to solve the problem of how to use energy efficiently.
A Hungarian team has created the first drones that can fly as a coordinated flock. The researchers watched as the ten autonomous robots took to the air in a field outside Budapest, zipping through the open sky, flying in formation or even following a leader, all without any central control.
Initiative, compromise force SEIU's agenda Statesman Journal “Health care is already quite complex, so negotiating and deliberating are really a superior way to do policy, even if you back away a little bit from your ideal position.” (Page 2 of 2).
Nobel Laureate In Economics Professor Joseph Stiglitz : The Innovation Enigma Jewish Business News In 1987, economist Robert Solow – awarded the Nobel Prize for his pioneering work on growth – lamented that “You can see the computer age everywhere...
The View Of Digital Health From An 'Engaged Patient' Forbes I have Type 1 diabetes [which is] very complex, very difficult to control – what they used to call “brittle” in the old days. So what does that mean?
Computer system simulates the behavior of tax evaders Phys.Org The simulator, described in the journal Advances in Complex Systems, analyzes the factors motivating tax evasion and allows to determine which measures are effective in reducing it,...
(Medical Xpress)—Although choosing to do something because the perceived benefit outweighs the financial cost is something people do daily, little is known about what happens in the brain when a person makes these kinds of decisions.
So far as I know no one has demonstrated any neural circuitry not adapted from pre-economic behavior used in the market place. This would imply that most economic postulates are wrong. Rationality is out the window as ...
Competition for attention among users can bring social networks close to the critical point of a phase transition.
A “meme” is an idea, style, or behavior that spreads within society; examples include songs, catch phrases, Internet videos, and fashions. The name was coined by British evolutionary biologist Richard Dawkins to suggest the analogy with a gene: a meme can replicate, mutate, and evolve, competing for success. But what mechanisms determine the popularity of a meme? Reporting in Physical Review Letters, James Gleeson at the University of Limerick, Ireland, and co-workers present a model that describes how memes spread and compete in a social network.
The key result of their analysis is that the competition between memes turns the social network into a so-called critical system, i.e., a system close to the critical point of a phase transition. In such a state, minor disturbances lead to avalanches of events that drive the system to a new phase, e.g., one in which certain memes go viral. As expected for a critical state, the authors show that many statistical properties exhibit certain regularities. In particular, they are able to predict distributions of popularity following power laws whose exponents are close to empirical values.
When animals swarm they exhibit a complex collective intelligence that could help us build robots, heal wounds and understand the brain.
We tend to think of swarms as mindless moving masses, not the kind of thoughtful groups that humans form. But humans often behave like a swarm, particularly when it comes to collective decision-making.
During election campaigns, people often believe that sufficiently outspoken minority groups have the power to sway the results. That's unlikely, say Iain Couzin and his team at Princeton University. Their models of voter swarms show that the minority influence, however strong, gets diluted to the point where the group goes with the majority decision – provided the electorate contains enough uninformed and undecided voters who simply copy their neighbours. For better or worse, ignorance plays a significant role in the way democracies operate.
Cities are increasingly the fundamental socio-economic units of human societies worldwide, but we still lack a unified characterization of urbanization that captures the social processes realized by cities across time and space. This is especially important for understanding the role of cities in the history of human civilization and for determining whether studies of ancient cities are relevant for contemporary science and policy. As a step in this direction, we develop a theory of settlement scaling in archaeology, deriving the relationship between population and settled area from a consideration of the interplay between social and infrastructural networks. We then test these models on settlement data from the Pre-Hispanic Basin of Mexico to show that this ancient settlement system displays spatial scaling properties analogous to those observed in modern cities. Our data derive from over 1,500 settlements occupied over two millennia and spanning four major cultural periods characterized by different levels of agricultural productivity, political centralization and market development. We show that, in agreement with theory, total settlement area increases with population size, on average, according to a scale invariant relation with an exponent in the range . As a consequence, we are able to infer aggregate socio-economic properties of ancient societies from archaeological measures of settlement organization. Our findings, from an urban settlement system that evolved independently from its old-world counterparts, suggest that principles of settlement organization are very general and may apply to the entire range of human history.
If advancing civilization relies on social networks, the world is in trouble. According to newly published research by University of Oregon psychologist Azim Shariff, individuals relying on their social groups can find solutions but also pre-empt the motivation for independent analytical thinking.
Social networks encompass many scenarios, from divisions within organizations, to fraternities and sororities, to connections on Facebook and Twitter. The four-member research team is not proclaiming a doomsday scenario; it is studying the impacts of social learning in networks from a broad cultural perspective.
While social learning "is a key cultural mechanism that improves the performance of individuals and groups," writes Shariff and international colleagues in the introduction of their paper placed online by the Journal of the Royal Society Interface, watching and copying others while seeking solutions has some limitations on analytical development that drives innovation.
It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.
Check out the following article by Emma Uprichard on Big Data! BIG DATA, LITTLE QUESTIONS? It is a great essay, as it points to the important and critical questions that folks, as of late, are not asking in real, sociologically ...
Virtual students offer crash course for teachers-in-training Milwaukee Journal Sentinel Many young teachers struggle with discipline and drop out of teaching because they become discouraged by classroom management issues, said Craig Berg, a UWM...