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Visualising the network of co-enrolled course subjects - Katy Jordan

Visualising the network of co-enrolled course subjects - Katy Jordan | Network and Graph Theory | Scoop.it

Have you ever wondered which MOOC courses students study together? I’ve been thinking recently about whether MOOC students choose to enrol in combinations of courses from the same subject area, or are more interdisciplinary in their studies.

To look into this, I looked at the combinations of courses listed on public Coursera profile pages. I collected the information in a spreadsheet and (using Gephi) made a network graph – where nodes represent courses, and a link is present if a student has enrolled on both courses (by doing this, the data is anonymised and doesn’t contain any information about students or links to their profiles). The links are weighted so that the more students who took these two courses together, the thicker the link is. I used the modularity algorithm in Gephi to try to detect communities within the network, and colour-coded the nodes to reflect this.

Thanks to a handy plugin for Gephi from Oxford Internet Institute, I’ve been able to create an interactive, online version of the graph to share, which you can view here (opens in a new window).

 

 

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Dynamical Systems on Networks: A Tutorial

Dynamical Systems on Networks: A Tutorial | Network and Graph Theory | Scoop.it

We give a tutorial for the study of dynamical systems on networks. We focus especially on "simple" situations that are tractable analytically, because they can be very insightful and provide useful springboards for the study of more complicated scenarios. We briefly motivate why examining dynamical systems on networks is interesting and important, and we then give several fascinating examples and discuss some theoretical results. We also briefly discuss dynamical systems on dynamical (i.e., time-dependent) networks, overview software implementations, and give an outlook on the field.

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A 1:1000 scale model of the digital world: Global connectivity can lead to the extinction of local networks

The overwhelming success of online social networks, the key actors in the cosmos of the Web 2.0, has reshaped human interactions on a worldwide scale. To understand the fundamental mechanisms which determine the fate of online social networks at the system level, we recently introduced a general ecological theory of the digital world. In this paper, we discuss the impact of heterogeneity in the network intrinsic fitness and present how the general theory can be applied to understand the competition between an international network, like Facebook, and local services. To this end, we construct a 1:1000 scale model of the digital world enclosing the 80 countries with most Internet users. We find that above a certain threshold the level of global connectivity can lead to the extinction of local networks. In addition, we reveal the complex role the tendency of individuals to engage in more active networks plays for the probability of local networks to become extinct and provide insights into the conditions under which they can prevail.

 

A 1:1000 scale model of the digital world: Global connectivity can lead to the extinction of local networks
Kaj-Kolja Kleineberg, Marian Boguna

http://arxiv.org/abs/1504.01368


Via Complexity Digest
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Rescooped by Bernard Ryefield from Complex Systems and X-Events
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Networks Reveal the Connections of Disease | Quanta Magazine

Networks Reveal the Connections of Disease |  Quanta Magazine | Network and Graph Theory | Scoop.it
Enormous databases of medical records have begun to reveal the hidden biological missteps that make us sick.

Via Roger D. Jones, PhD
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Rescooped by Bernard Ryefield from Non-Equilibrium Social Science
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Systematic inequality and hierarchy in faculty hiring networks

The faculty job market plays a fundamental role in shaping research priorities, educational outcomes, and career trajectories among scientists and institutions. However, a quantitative understanding of faculty hiring as a system is lacking. Using a simple technique to extract the institutional prestige ranking that best explains an observed faculty hiring network—who hires whose graduates as faculty—we present and analyze comprehensive placement data on nearly 19,000 regular faculty in three disparate disciplines. Across disciplines, we find that faculty hiring follows a common and steeply hierarchical structure that reflects profound social inequality. Furthermore, doctoral prestige alone better predicts ultimate placement than a U.S. News & World Report rank, women generally place worse than men, and increased institutional prestige leads to increased faculty production, better faculty placement, and a more influential position within the discipline. These results advance our ability to quantify the influence of prestige in academia and shed new light on the academic system.

 

Systematic inequality and hierarchy in faculty hiring networks
Aaron Clauset, Samuel Arbesman, Daniel B. Larremore

Science Advances 01 Feb 2015: Vol. 1 no. 1 e1400005

http://dx.doi.org/10.1126/sciadv.1400005 ;


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Représenter les généalogies intellectuelles : des Successions à Wikidata | Sciences communes

Représenter les généalogies intellectuelles : des Successions à Wikidata | Sciences communes | Network and Graph Theory | Scoop.it

C'est une obsession ancienne. Dès le IIIe siècle avant notre ère, des Successions de philosophes dressent la généalogie des relations entre maîtres et élèves.

L'obsession est encore bien vivante dans certaines disciplines. Mathématiciens, astronomes et chimistes tiennent ainsi à jour des bases de données de généalogie universitaire ; ils en tirent parfois des indices de proximité (ainsi, l'indice d'Erdös, qui désigne le degré de distance de tel mathématicien avec Paul Erdös). Ces initiatives restent partielles : elles sont cantonnées à une seule culture disciplinaire.

Le projet Wikidata permet d'aller au-delà : il aspire à composer une base de connaissance universelle. Sa communauté améliore et reformule continuellement une ontologie couvrant la totalité du savoir humain. Elle a ainsi créé depuis quelques mois une catégorie "étudiant de" (alias P1066), qui permet de signaler que X a étudié avec Y.

C'est ainsi que l'obsession m'a pris.

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The small-world effect is a modern phenomenon

The small-world effect is a modern phenomenon | Network and Graph Theory | Scoop.it

The "small-world effect" is the observation that one can find a short chain of acquaintances, often of no more than a handful of individuals, connecting almost any two people on the planet. It is often expressed in the language of networks, where it is equivalent to the statement that most pairs of individuals are connected by a short path through the acquaintance network. Although the small-world effect is well-established empirically for contemporary social networks, we argue here that it is a relatively recent phenomenon, arising only in the last few hundred years: for most of mankind's tenure on Earth the social world was large, with most pairs of individuals connected by relatively long chains of acquaintances, if at all. Our conclusions are based on observations about the spread of diseases, which travel over contact networks between individuals and whose dynamics can give us clues to the structure of those networks even when direct network measurements are not available. As an example we consider the spread of the Black Death in 14th-century Europe, which is known to have traveled across the continent in well-defined waves of infection over the course of several years. Using established epidemiological models, we show that such wave-like behavior can occur only if contacts between individuals living far apart are exponentially rare. We further show that if long-distance contacts are exponentially rare, then the shortest chain of contacts between distant individuals is on average a long one. The observation of the wave-like spread of a disease like the Black Death thus implies a network without the small-world effect.


Via Claudia Mihai, Complejidady Economía
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Network Effects on Scientific Collaborations

Network Effects on Scientific Collaborations | Network and Graph Theory | Scoop.it

Measures of social network analysis, for example network centrality and tie strength, have been utilized extensively in current co-authorship literature to explore different behavioural patterns of co-authorship networks. Using three SNA measures (i.e., degree centrality, closeness centrality and betweenness centrality), we explore scientific collaboration networks to understand factors influencing performance (i.e., citation count) and formation (tie strength between authors) of such networks. A citation count is the number of times an article is cited by other articles. We use co-authorship dataset of the research field of ‘steel structure’ for the year 2005 to 2009. To measure the strength of scientific collaboration between two authors, we consider the number of articles co-authored by them. In this study, we examine how citation count of a scientific publication is influenced by different centrality measures of its co-author(s) in a co-authorship network. We further analyze the impact of the network positions of authors on the strength of their scientific collaborations. We use both correlation and regression methods for data analysis leading to statistical validation. We identify that citation count of a research article is positively correlated with the degree centrality and betweenness centrality values of its co-author(s). Also, we reveal that degree centrality and betweenness centrality values of authors in a co-authorship network are positively correlated with the strength of their scientific collaborations.

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The Social Network of Alexander the Great: Social Network Analysis in Ancient History

The Social Network of Alexander the Great: Social Network Analysis in Ancient History | Network and Graph Theory | Scoop.it
The Social Network of Alexander the Great: Social Network Analysis in Ancient History
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Information, Meaning, and Intellectual Organization in Networks of Inter-Human Communication

The Shannon-Weaver model of linear information transmission is extended with two loops potentially generating redundancies: (i) meaning is provided locally to the information from the perspective of hindsight, and (ii) meanings can be codified differently and then refer to other horizons of meaning. Thus, three layers are distinguished: variations in the communications, historical organization at each moment of time, and evolutionary self-organization of the codes of communication over time. Furthermore, the codes of communication can functionally be different and then the system is both horizontally and vertically differentiated. All these subdynamics operate in parallel and necessarily generate uncertainty. However, meaningful information can be considered as the specific selection of a signal from the noise; the codes of communication are social constructs that can generate redundancy by giving different meanings to the same information. Reflexively, one can translate among codes in more elaborate discourses. The second (instantiating) layer can be operationalized in terms of semantic maps using the vector space model; the third in terms of mutual redundancy among the latent dimensions of the vector space. Using Blaise Cronin's {\oe}uvre, the different operations of the three layers are demonstrated empirically.

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Rising Tides or Rising Stars?: Dynamics of Shared Attention on Twitter during Media Events

Rising Tides or Rising Stars?: Dynamics of Shared Attention on Twitter during Media Events | Network and Graph Theory | Scoop.it
PLOS ONE: an inclusive, peer-reviewed, open-access resource from the PUBLIC LIBRARY OF SCIENCE. Reports of well-performed scientific studies from all disciplines freely available to the whole world.
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Rescooped by Bernard Ryefield from Complexity - Complex Systems Theory
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▶ Large-Scale Structure in Networks - YouTube

▶ Large-Scale Structure in Networks - YouTube | Network and Graph Theory | Scoop.it
Mark Newman May 2, 2014 Annual Science Board Symposium and Meeting Complexity: Theory and Practice
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Eli Levine's curator insight, June 9, 2014 2:40 AM

To know the structure is to know a HUMONGOUS part of the function and, thus, the ability to predict.  It seems to me to be a large fractal pattern of clusters, nodes and connections (but, that is just in my relatively uneducated eye). 

 

Never forget, though, that there are important qualitative aspects to networks (think of defacto qualities of the nodes, groups of nodes and the connections amongst them).  Very important for social and/or ecological/causal relation networks (essentially, a network that outlines and maps accurately the function of a system and all of the flows of information and material resources).

 

Really cool stuff here.

 

Think about it..

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Predicting Successful Memes using Network and Community Structure v2

We investigate the predictability of successful memes using their early spreading patterns in the underlying social networks. We propose and analyze a comprehensive set of features and develop an accurate model to predict future popularity of a meme given its early spreading patterns. Our paper provides the first comprehensive comparison of existing predictive frameworks. We categorize our features into three groups: influence of early adopters, community concentration, and characteristics of adoption time series. We find that features based on community structure are the most powerful predictors of future success. We also find that early popularity of a meme is not a good predictor of its future popularity, contrary to common belief. Our methods outperform other approaches, particularly in the task of detecting very popular or unpopular memes.

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Network Science by Albert-László Barabási

Network Science by Albert-László Barabási | Network and Graph Theory | Scoop.it

Network Science, a textbook for network science, is freely available under the Creative Commons licence. Follow its development onFacebook, Twitter or by signining up to our mailing list, so that we can notify you of new chapters and developments.

The book is the result of a collaboration between a number of individuals, shaping everything, from content (Albert-László Barabási), to visualizations and interactive tools (Gabriele Musella,Mauro Martino, Nicole Samay, Kim Albrecht), simulations and data analysis (Márton Pósfai). The printed version of the book will be published by Cambridge University Press in 2015. In the coming months the website will be expanded with an interactive version of the text, datasets, and slides to teach the material.

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Topology and evolution of the network of western classical music composers

Topology and evolution of the network of western classical music composers | Network and Graph Theory | Scoop.it
The expanding availability of high-quality, large-scale data from the realm of culture and the arts promises novel opportunities for understanding and harnessing the dynamics of the creation, collaboration, and dissemination processes - fundamentally network phenomena - of artistic works and styles. To this end, in this paper we explore the complex network of western classical composers constructed from a comprehensive CD (Compact Disc) recordings data that represent the centuries-old musical tradition using modern data analysis and modeling techniques. We start with the fundamental properties of the network such as the degree distribution and various centralities, and find how they correlate with composer attributes such as artistic styles and active periods, indicating their significance in the formation and evolution of the network. We also investigate the growth dynamics of the network, identifying superlinear preferential attachment as a major growth mechanism that implies a future of the musical landscape where an increasing concentration of recordings onto highly-recorded composers coexists with the diversity represented by the growth in the sheer number of recorded composers. Our work shows how the network framework married with data can be utilized to advance our understanding of the underlying principles of complexities in cultural systems.
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Voting Behaviour and Power in Online Democracy: A Study of LiquidFeedback in Germany's Pirate Party

In recent years, political parties have adopted Online Delegative Democracy platforms such as LiquidFeedback to organise themselves and their political agendas via a grassroots approach. A common objection against the use of these platforms is the delegation system, where a user can delegate his vote to another user, giving rise to so-called super-voters, i.e. powerful users who receive many delegations. It has been asserted in the past that the presence of these super-voters undermines the democratic process, and therefore delegative democracy should be avoided. In this paper, we look at the emergence of super-voters in the largest delegative online democracy platform worldwide, operated by Germany's Pirate Party. We investigate the distribution of power within the party systematically, study whether super-voters exist, and explore the influence they have on the outcome of votings conducted online. While we find that the theoretical power of super-voters is indeed high, we also observe that they use their power wisely. Super-voters do not fully act on their power to change the outcome of votes, but they vote in favour of proposals with the majority of voters in many cases thereby exhibiting a stabilising effect on the system. We use these findings to present a novel class of power indices that considers observed voting biases and gives significantly better predictions than state-of-the-art measures.

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Emergence of Super Cooperation of Prisoner’s Dilemma Games on Scale-Free Networks

Emergence of Super Cooperation of Prisoner’s Dilemma Games on Scale-Free Networks | Network and Graph Theory | Scoop.it

Recently, the authors proposed a quantum prisoner’s dilemma game based on the spatial game of Nowak and May, and showed that the game can be played classically. By using this idea, we proposed three generalized prisoner’s dilemma (GPD, for short) games based on the weak Prisoner’s dilemma game, the full prisoner’s dilemma game and the normalized Prisoner’s dilemma game, written by GPDW, GPDF and GPDN respectively. Our games consist of two players, each of which has three strategies: cooperator (C), defector (D) and super cooperator (denoted by Q), and have a parameter γ to measure the entangled relationship between the two players. We found that our generalised prisoner’s dilemma games have new Nash equilibrium principles, that entanglement is the principle of emergence and convergence (i.e., guaranteed emergence) of super cooperation in evolutions of our generalised prisoner’s dilemma games on scale-free networks, that entanglement provides a threshold for a phase transition of super cooperation in evolutions of our generalised prisoner’s dilemma games on scale-free networks, that the role of heterogeneity of the scale-free networks in cooperations and super cooperations is very limited, and that well-defined structures of scale-free networks allow coexistence of cooperators and super cooperators in the evolutions of the weak version of our generalised prisoner’s dilemma games.

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EPJ Data Science | Full text | The nature and evolution of online food preferences

Food is a central element of humans’ life, and food preferences are amongst others manifestations of social, cultural and economic forces that influence the way we view, prepare and consume food. Historically, data for studies of food preferences stems from consumer panels which continuously capture food consumption and preference patterns from individuals and households. In this work we look at a new source of data, i.e., server log data from a large recipe platform on the World Wide Web, and explore its usefulness for understanding online food preferences. The main findings of this work are: (i) recipe preferences are partly driven by ingredients, (ii) recipe preference distributions exhibit more regional differences than ingredient preference distributions, and (iii) weekday preferences are clearly distinct from weekend preferences.
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Inuit Genealogy

Inuit Genealogy | Network and Graph Theory | Scoop.it
The diagram above is a genealogical diagram made in the mid 1950s by anthropologist Jean Malaurie, the first of its kind. It’s a hand made radial drawing, Malaurie has a whole series of them in his apartment in Paris, along with his extensive personal archive of research materials including photos, films, notebooks, drawings.
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Rescooped by Bernard Ryefield from Complexity - Complex Systems Theory
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Global Civil Unrest: Contagion, Self-Organization, and Prediction

Global Civil Unrest: Contagion, Self-Organization, and Prediction | Network and Graph Theory | Scoop.it

Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, records of civil unrest of 170 countries during the period 1919–2008 are analyzed. It is demonstrated that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.

 

 

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Multilayer networks

Multilayer networks | Network and Graph Theory | Scoop.it

In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time and include other types of complications. Such systems include multiple subsystems and layers of connectivity, and it is important to take such ‘multilayer’ features into account to try to improve our understanding of complex systems. Consequently, it is necessary to generalize ‘traditional’ network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. The origins of such efforts date back several decades and arose in multiple disciplines, and now the study of multilayer networks has become one of the most important directions in network science. In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks. To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other and provide a thorough discussion that compares, contrasts and translates between related notions such as multilayer networks, multiplex networks, interdependent networks, networks of networks and many others. We also survey and discuss existing data sets that can be represented as multilayer networks. We review attempts to generalize single-layer-network diagnostics to multilayer networks. We also discuss the rapidly expanding research on multilayer-network models and notions like community structure, connected components, tensor decompositions and various types of dynamical processes on multilayer networks. We conclude with a summary and an outlook.

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Online Social Networks: Threats and Solutions

Many online social network (OSN) users are unaware of the numerous security risks that exist in these networks, including privacy violations, identity theft, and sexual harassment, just to name a few. According to recent studies, OSN users readily expose personal and private details about themselves, such as relationship status, date of birth, school name, email address, phone number, and even home address. This information, if put into the wrong hands, can be used to harm users both in the virtual world and in the real world. These risks become even more severe when the users are children. In this paper we present a thorough review of the different security and privacy risks which threaten the well-being of OSN users in general, and children in particular. In addition, we present an overview of existing solutions that can provide better protection, security, and privacy for OSN users. We also offer simple-to-implement recommendations for OSN users which can improve their security and privacy when using these platforms. Furthermore, we suggest future research directions.

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The Strange Evolution of Self Obsession on Reddit — The Physics arXiv Blog — Medium

The Strange Evolution of Self Obsession on Reddit — The Physics arXiv Blog — Medium | Network and Graph Theory | Scoop.it
The self-proclaimed frontpage of the internet has grown exponentially in just a few years.
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Human Genome Variation and the Concept of Genotype Networks

Human Genome Variation and the Concept of Genotype Networks | Network and Graph Theory | Scoop.it
PLOS ONE: an inclusive, peer-reviewed, open-access resource from the PUBLIC LIBRARY OF SCIENCE. Reports of well-performed scientific studies from all disciplines freely available to the whole world.
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ECCS 2014 Living Satellite

ECCS 2014 Living Satellite | Network and Graph Theory | Scoop.it

Workshop on Robustness, Adaptability and Critical Transitions in Living Systems.Call for papers http://seis.bristol.ac.uk/~fs13378/eccs_2014_livingsys.html

 

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