The Emerging Science of Superspreaders (And How to Tell If You're One Of Them) Who are the most influential spreaders of information on a network? That’s a question that marketers, bloggers, news services and even governments would like answered. Not least because the answer could provide ways to promote products quickly, to boost the popularity of political parties above their rivals and to seed the rapid spread of news and opinions. So it’s not surprising that network theorists have spent some time thinking about how best to identify these people and to check how the information they receive might spread around a network. Indeed, they’ve found a number of measures that spot so-called superspreaders, people who spread information, ideas or even disease more efficiently than anybody else. But there’s a problem. But there is growing evidence that information does not spread through real networks in the same way as it does through these idealised ones. So the question of how to find the superspreaders remains open.
Social Constructivist Theories For a general intro to constructivism click: Overview of constructivism. Overview of Social Constructivism Another cognitive psychologist, Lev Vygotsky ( shared many of Piaget's ( assumptions about how children learn, but he placed more emphasis on the social context of learning. Piaget's cognitive theories have been used as the foundation for discovery learning ( models in which the teacher plays a limited role. There is a great deal of overlap between cognitive constructivism and Vygotsky's social constructivist theory. Although Vygotsky died at the age of 38 in 1934, most of his publications did not appear in English until after 1960. We call Vygotsky's brand of constructivism social constructivism because he emphasized the critical importance of culture and the importance of the social context for cognitive development. 1.
Visualizing Your Facebook Network with Gephi | Social DynamicsSocial Dynamics This is a visualization of my own Facebook network that I made using the (free) software Gephi and the Facebook application netvizz. Each node in the network is one of my Facebook friends, and two friends are connected to one another if they are Facebook friends with each other. The size of the node corresponds to the "degree" of the node, which means how many connections it has. In this case, that means how many of my Facebook friends that person is Facebook friends with. (Note: I deleted the names from the nodes to protect my Facebook friends' privacy). The colors of the nodes indicate communities of friends found using a clustering algorithm based on the "modularity" of the network. We did this as an exercise in the Social Dynamics and Networks course that I teach at Kellogg.
Measuring Large-Scale Social Networks with High Resolution This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. Figures Editor: Yamir Moreno, University of Zaragoza, Spain Copyright: © 2014 Stopczynski et al.
Seppuku Illustration from Sketches of Japanese Manners and Customs, by J. M. W. Silver, Illustrated by Native Drawings, Reproduced in Facsimile by Means of Chromolithography, London, 1867 Seppuku with ritual attire and second (staged) Samurai about to perform seppuku Seppuku (切腹? Vocabulary and etymology[edit] Seppuku is also known as harakiri (腹切り, "cutting the belly"),[3] a term more widely familiar outside Japan, and which is written with the same kanji as seppuku, but in reverse order with an okurigana. "It is commonly pointed out that hara-kiri is a vulgarism, but this is a misunderstanding. The practice of committing seppuku at the death of one's master, known as oibara (追腹 or 追い腹, the kun'yomi or Japanese reading) or tsuifuku (追腹, the on'yomi or Chinese reading), follows a similar ritual. The word jigai (自害?) Overview[edit] A tantō prepared for seppuku Ritual[edit] In time, carrying out seppuku came to involve a detailed ritual. The second was usually, but not always, a friend. History[edit]
The Remarkable Properties of Mythological Social Networks Ten years ago, few people would have heard of a social network. Today, Facebook, Twitter and LinkedIn permeate our lives. They show us how we are linked to each other and how we are more broadly placed within society. What fascinates scientists is that the general properties of social networks seem to be invariant regardless of where they crop up. For example, one of the remarkable properties of social networks is their small world character. That was entirely unexpected and counterintuitive when it was discovered in the 1960s by the American social psychologist Stanley Milgram. Today, P J Miranda at the Federal Technological University of Paraná in Brazil and a couple of pals study the social network between characters in Homer’s ancient Greek poem the Odyssey. Miranda and co think of each character in the Odyssey as a node in the network. In analysing the Odyssey, they identified 342 unique characters and over 1,700 relations between them.
Facebook feelings are contagious: Study examines how emotions spread online You can’t catch a cold from a friend online. But can you catch a mood? It would seem so, according to new research from the University of California, San Diego. Published in PLOS ONE, the study analyzes over a billion anonymized status updates among more than 100 million users of Facebook in the United States. Positive posts beget positive posts, the study finds, and negative posts beget negative ones, with the positive posts being more influential, or more contagious. “Our study suggests that people are not just choosing other people like themselves to associate with but actually causing their friends’ emotional expressions to change,” said lead author James Fowler, professor of political science in the Division of Social Sciences and of medical genetics in the School of Medicine at UC San Diego. There is abundant scientific literature on how emotion can spread among people – through direct contact, in person – not only among friends but also among strangers or near-strangers.
Systèmes dynamiques et équations différentielles Un système dynamique est en effet un ensemble d’entités en interaction. Du fait même de ces interactions, la valeur de grandeurs attachées à ces entités évolue dans le temps. C'est en étudiant l'évolution de ces valeurs que l'on cherche à comprendre et à prédire le comportement de ces systèmes. Cela repose sur leur représentation mathématique à l’aide d’équations différentielles. Dans l’exemple de la masselotte accrochée à un ressort, la grandeur dont la valeur évolue peut être la distance de son centre de gravité à sa position au repos. À chacune de ces grandeurs, il est possible d’associer une variable dont la valeur change en fonction du temps. Une valeur n’a de sens que si l’unité dans laquelle elle est exprimée est précisée. Disposant de connaissances sur les interactions entre les diverses entités qui composent le système étudié, est-il possible de comprendre comment les valeurs de ces variables évoluent dans le temps, et par là-même, de comprendre le comportement du système ? .
How to Find the Best Connected Individual in Your Social Network The study of networks has exploded in recent years. Network scientists have measured, simulated, kicked and prodded almost every social network under the sun. And in doing so, they’ve discovered all kinds of fascinating properties of these networks, properties that allow them to better understand the spread information and the role that people play in this process. In particular, theorists have long known that better connected individuals play more important roles in a network because they allow information to spread more efficiently. It’s easy to imagine that mere humans have always been largely ignorant of these networks, given the complexity of these webs and the complicated measures needed to calculate the connectedness of each node within in them. Now Abhijit Banerjee at MIT and a few pals say there is a better way that is faster and cheaper. Banerjee and co made their discovery by studying the network of links between individuals in 75 rural villages in southwest India.