Core percolation is a fundamental structural transition in complex networks related to a wide range of important problems. Recent advances have provided us an analytical framework of core percolation in uncorrelated random networks with arbitrary degree distributions. Here we apply the tools in analysis of network controllability. We confirm analytically that the emergence of the bifurcation in control coincides with the formation of the core and the structure of the core determines the control mode of the network. We also derive the analytical expression related to the controllability robustness by extending the deduction in core percolation. These findings help us better understand the interesting interplay between the structural and dynamical properties of complex networks.
A number of predictors have been suggested to detect the most influential spreaders of information in online social media across various domains such as Twitter or Facebook. In particular, degree, PageRank, k-core and other centralities have been adopted to rank the spreading capability of users in information dissemination media. So far, validation of the proposed predictors has been done by simulating the spreading dynamics rather than following real information flow in social networks. Consequently, only model-dependent contradictory results have been achieved so far for the best predictor. Here, we address this issue directly. We search for influential spreaders by following the real spreading dynamics in a wide range of networks. We find that the widely-used degree and PageRank fail in ranking users' influence. We find that the best spreaders are consistently located in the k-core across dissimilar social platforms such as Twitter, Facebook, Livejournal and scientific publishing in the American Physical Society. Furthermore, when the complete global network structure is unavailable, we find that the sum of the nearest neighbors' degree is a reliable local proxy for user's influence. Our analysis provides practical instructions for optimal design of strategies for [ldquo]viral[rdquo] information dissemination in relevant applications.
The European Commission has launched a public consultation on ‘Science 2.0’, in order to gauge the trend towards a more open, data-driven and people-focused way of doing research and innovation. Researchers are using digital tools to get thousands of people participating
Complex Adaptive Systems Modeling welcomes submissions to the new thematic series on Modeling large-scale communication networks using complex networks and agent-based modeling techniques. This thematic series intends to publish high quality original research as well as review articles on case studies, models and methods for the modeling and simulation of large-scale computer communication networks using either of the following two approaches:
Complex networks (such as modeled using tools such as Gephi, Network Workbench and others) Agent-based models (such as based on NetLogo, Repast, Mason, Swarm and others)
Modelling the behaviour of stock markets has been of major interest in the past century. The market can be treated as a network of many investors reacting in accordance to their group behaviour, as manifested by the index and effected by the flow of external information into the system. Here we devise a model that encapsulates the behaviour of stock markets. The model consists of two terms, demonstrating quantitatively the effect of the individual tendency to follow the group and the effect of the individual reaction to the available information. Using the above factors we were able to explain several key features of the stock market: the high correlations between the individual stocks and the index; the Epps effect; the high fluctuating nature of the market, which is similar to real market behaviour. Furthermore, intricate long term phenomena are also described by this model, such as bursts of synchronized average correlation and the dominance of the index as demonstrated through partial correlation.
"Stanford computer scientists have created a website to help organizers plan events that are more likely to succeed or allow them to pull the plug on impending flops before they occur.
The website, called Catalyst, is based on a behavioral science concept known as the threshold model of collective action, which posits that people may be reluctant to commit to participating in activity until they see others taking part, at which point interest surges and the activity becomes successful. But if participation doesn’t reach this threshold point, the event is likely to fail.
Catalyst builds this principle into software. The website allows people to enter a few details, such as date, time, description of the event and the number of participants needed to make it a success. If signups don't hit this threshold point by the deadline, Catalyst emails organizers and would-be participants a warning."
We have become familiar with the concept of climate change as greenhouse gases accumulate in the atmosphere and cause average global temperature to rise. No less than182 nations have agreed to cut their greenhouse gas emissions by ratifying the Kyoto Protocol, which entered into force in 2005 and is due to expire at the end of 2012. However, what do human rights — the rights we all have as human beings — have to do with climate change? Surprisingly, quite a lot, and the impacts are both direct and indirect. Many economic, social and cultural rights are impacted by climate change, including the rights to food, water, housing and health. Civil and political rights, such as the right to life, and the cultural rights of Indigenous people can also be impacted by climate change. This article examines these impacts,with a particular emphasis on Australia.
Digital Humanities is a convergence of humanities fields (linguistic, history, psychology…) using data archives, processing and interaction. Data mining is an interdisciplinary subfield of computer science, involving the methods at the intersection of artificial intelligence, machine learning and database systems. The Journal of Data Mining & Digital Humanities is concerned with the intersection of computing and the disciplines of the humanities, with tools provided by computing such as data visualisation, information retrieval, statistics, text mining by publishing scholarly work beyond the traditional humanities.
In 1953, at the dawn of modern computing, Nils Aall Barricelli played God. Clutching a deck of playing cards in one hand and a stack
of punched cards in the other, Barricelli hovered over one of the world’s earliest and most influential computers, the IAS machine, at the Institute for Advanced Study in Princeton, New Jersey. During the day the computer was used to make weather forecasting calculations; at night it was commandeered by the Los Alamos group to calculate ballistics for nuclear weaponry. Barricelli, a maverick mathematician, part Italian and part Norwegian, had finagled time on the computer to model the origins and evolution of life.
By Rana D. Parshad, Vineeta Chand, Neha Sinha, Nitu Kumari
While language competition models of diachronic language shift are increasingly sophisticated, drawing on sociolinguistic components like variable language prestige, distance from language centers and intermediate bilingual transitionary populations, in one significant way they fall short. They fail to consider contact-based outcomes resulting in mixed language practices, e.g. outcome scenarios such as creoles or unmarked code switching as an emergent communicative norm. On these lines something very interesting is uncovered in India, where traditionally there have been monolingual Hindi speakers and Hindi/English bilinguals, but virtually no monolingual English speakers. While the Indian census data reports a sharp increase in the proportion of Hindi/English bilinguals, we argue that the number of Hindi/English bilinguals in India is inaccurate, given a new class of urban individuals speaking a mixed lect of Hindi and English, popularly known as "Hinglish". Based on predator-prey, sociolinguistic theories, salient local ecological factors and the rural-urban divide in India, we propose a new mathematical model of interacting monolingual Hindi speakers, Hindi/English bilinguals and Hinglish speakers. The model yields globally asymptotic stable states of coexistence, as well as bilingual extinction. To validate our model, sociolinguistic data from different Indian classes are contrasted with census reports: We see that purported urban Hindi/English bilinguals are unable to maintain fluent Hindi speech and instead produce Hinglish, whereas rural speakers evidence monolingual Hindi. Thus we present evidence for the first time where an unrecognized mixed lect involving English but not "English", has possibly taken over a sizeable faction of a large global population.
A real socio-economic system can be also identified by territorial and social boundaries: a city, a region etc. The actors therein operating are firms, markets, industrial clusters and are embedded in regional and national innovation systems. An emerging approach identifies the socio-economic system as a ‘smart territory’ characterised by the flow of citizens; the domain of interest is that of public services. Smart territories require business integrated services and long term sustainability, whilst their governance require 2.0 making tools, enabling the sharing of targets between policy makers, innovation and growth strategies and monitoring.
The general idea of this satellite is that these advances can significantly enhance evolutionary explanations of dynamic economic phenomena, and that as complex adaptive systems (CAS) theory constitutes the appropriate analytical framework within which analyse the evolution of socio-economic systems. CAS theory is increasingly being used in socio-economic contexts since the widely accepted view that all social and economic systems are complex adaptive systems has led to important advances on how the general properties of CAS are translated or understood in the economic and the organizational fields.
‘Causal’ direction is of great importance when dealing with complex systems. Often big volumes of data in the form of time series are available and it is important to develop methods that can inform about possible causal connections between the different observables. Here we investigate the ability of the Transfer Entropy measure to identify causal relations embedded in emergent coherent correlations. We do this by firstly applying Transfer Entropy to an amended Ising model. In addition we use a simple Random Transition model to test the reliability of Transfer Entropy as a measure of ‘causal’ direction in the presence of stochastic fluctuations. In particular we systematically study the effect of the finite size of data sets.
Campaigners against the use of journal impact factors as a proxy for research excellence received a shot in the arm last night with the launch of the San Francisco Declaration on Research Assessment (DORA). With an impressive line-up of founding signatories, including individual scientists, research funders and journal editors, DORA states in no uncertain terms that journal impact factors (which rank journals by the average number of citations their articles receive over a given period) should not be used "as a surrogate measure of the quality of individual research articles, to assess an individual scientist's contribution, or in hiring, promotion or funding decisions."
Facebook has been experimenting on us. A new paper in the Proceedings of the National Academy of Sciences reveals that Facebook intentionally manipulated the news feeds of almost 700,000 users in order to study “emotional contagion through social networks.” The study raises a number of ethics and privacy issues, since no authorization or warning was issued for the experiment.
Color is a crucial part of our visual experience. It indicates many things in our lives, from the ripeness of a banana, to how someone is feeling, to which subway line we should be on. Not everyone sees colors the same way, and colors have drastically different meanings in different cultures, but one thing we all have in common: color is important. These visualizations all show us different things about colors. Let’s start with the Meaning of Colors in Different Cultures. What Colors Mean in Different Cultures infographic And the Psychology of Color depends somewhat on culture, but some of it goes deeper than that, as we can see by multiple cultures tying similar meanings to similar colors. The Psychology of Color infographic by Dehahs. You can be certain that big companies know this, and they choose their colors wisely based on that psychology. So, what are the... keep reading
Have you ever felt like you're talking, but nobody is listening? Here's Julian Treasure to help. In this useful talk, the sound expert demonstrates the how-to's of powerful speaking — from some handy vocal exercises to tips on how to speak with empathy. A talk that might help the world sound more beautiful.
Alex Pentland says data, sensors and smartphones are opening the door to what he calls “social physics.” It is the subject of his new book, about the implications of being able to monitor and measure the flow of ideas in companies, markets and communities as never before. The payoff, he says, should be the acceleration of the pace of innovation.
This book explores the view that normative behaviour is part of a complex of social mechanisms, processes and narratives that are constantly shifting. From this perspective, norms are not a kind of self-contained social object or fact, but rather an interplay of many things that we label as norms when we ‘take a snapshot’ of them at a particular instant. Further, this book pursues the hypothesis that considering the dynamic aspects of these phenomena sheds new light on them.
Absolutely the best thing to read on the corporate hype and innuendos from the big computer companies pedalling the idea of ‘the smart city’. Adam Greenfield’s new book – that you can only get on Kindle and which was my first Kindle purchase that I read on my iPad (a success I must say) – is a wonderful and eloquent essay on the extreme hype surrounding the top down new town-like smart cities of Songdo (in South Korea), Masdar (in the UAE), PlanIT Valley (near Paredes in Portugal). He also comments on Singapore, Rio de Janeiro and some of the other established cities who are injecting automation into their urban services and other functions from the top down. His message is that most of the smart cities hype associated with IBM, Cisco, and Siemens amongst others which he recounts in detail is based on the most simplistic of notions as to what a city actually is.
An understanding of how individuals shape and impact the evolution of society is vastly limited due to the unavailability of large-scale reliable datasets that can simultaneously capture information regarding individual movements and social interactions. We believe that the popular Indian film industry, “Bollywood”, can provide a social network apt for such a study. Bollywood provides massive amounts of real, unbiased data that spans more than 100 years, and hence this network has been used as a model for the present paper. The nodes which maintain a moderate degree or widely cooperate with the other nodes of the network tend to be more fit (measured as the success of the node in the industry) in comparison to the other nodes. The analysis carried forth in the current work, using a conjoined framework of complex network theory and random matrix theory, aims to quantify the elements that determine the fitness of an individual node and the factors that contribute to the robustness of a network. The authors of this paper believe that the method of study used in the current paper can be extended to study various other industries and organizations.
by Konglin Zhu, Wenzhong Li, Xiaoming Fu, Jan Nagler
Online social networks such as Facebook, Twitter and Gowalla allow people to communicate and interact across borders. In past years online social networks have become increasingly important for studying the behavior of individuals, group formation, and the emergence of online societies. Here we focus on the characterization of the average growth of online social networks and try to understand which are possible processes behind seemingly long-range temporal correlated collective behavior. In agreement with recent findings, but in contrast to Gibrat's law of proportionate growth, we find scaling in the average growth rate and its standard deviation. In contrast, Renren and Twitter deviate, however, in certain important aspects significantly from those found in many social and economic systems. Whereas independent methods suggest no significance for temporally long-range correlated behavior for Renren and Twitter, a scaling analysis of the standard deviation does suggest long-range temporal correlated growth in Gowalla. However, we demonstrate that seemingly long-range temporal correlations in the growth of online social networks, such as in Gowalla, can be explained by a decomposition into temporally and spatially independent growth processes with a large variety of entry rates. Our analysis thus suggests that temporally or spatially correlated behavior does not play a major role in the growth of online social networks.