recentpopularlog in

tsuomela : network-analysis   54

Home - Matthew Lincoln, PhD
"I am a data research specialist at the Getty Research Institute, where I use computer-aided analysis of cultural datasets to help model long-term trends in iconography, art markets, and the social relations between artists."
weblog-individual  history  art  network-analysis  people  digital-humanities 
november 2017 by tsuomela
vis.js - A dynamic, browser based visualization library.
"A dynamic, browser based visualization library. The library is designed to be easy to use, to handle large amounts of dynamic data, and to enable manipulation of and interaction with the data. The library consists of the components DataSet, Timeline, Network, Graph2d and Graph3d."
network-analysis  networks  visualization  software  web  javascript  library 
may 2016 by tsuomela
NodeXL: Network Overview, Discovery and Exploration for Excel
"NodeXL is a free, open-source template for Microsoft® Excel® 2007 and 2010 that makes it easy to explore network graphs. "
network-analysis  networks  microsoft  software  visualization  analysis  graphics 
august 2012 by tsuomela
Network Interventions - Science Magazine 6 July 2012
The term “network interventions” describes the process of using social network data to accelerate behavior change or improve organizational performance. In this Review, four strategies for network interventions are described, each of which has multiple tactical alternatives. Many of these tactics can incorporate different mathematical algorithms. Consequently, researchers have many intervention choices at their disposal. Selecting the appropriate network intervention depends on the availability and character of network data, perceived characteristics of the behavior, its existing prevalence, and the social context of the program.
networks  network-analysis  intervention  research 
july 2012 by tsuomela
Identifying Influential and Susceptible Members of Social Networks
"Identifying social influence in networks is critical to understanding how behaviors spread. We present a method for identifying influence and susceptibility in networks that avoids biases in traditional estimates of social contagion by leveraging in vivo randomized experimentation. Estimation in a representative sample of 1.3 million Facebook users showed that younger users are more susceptible than older users, men are more influential than women, women influence men more than they influence other women, and married individuals are the least susceptible to influence in the decision to adopt the product we studied. Analysis of influence and susceptibility together with network structure reveals that influential individuals are less susceptible to influence than non-influential individuals and that they cluster in the network, which suggests that influential people with influential friends help spread this product."
social-networks  experiments  influence  random  statistics  models  network-analysis 
june 2012 by tsuomela
UnderstandingSociety: Social networks as aggregators
"This passage emphasizes quite a few themes that have been important throughout UnderstandingSociety -- the heterogeneity of social phenomena, the difficulty of formulating a clear understanding of social ontology, and the challenge of representing the processes of aggregation through which individual social actions contribute to mid- and large-scale social outcomes.

So how do the analytical resources of network theory contribute to a better understanding of the ways that actions aggregate into outcomes?"
sociology  social  theory  objects  network-analysis  networks  scale 
april 2011 by tsuomela
Cormode - A manifesto for modeling and measurement in social media - First Monday - 6 September 2010
Online social networks (OSNs) have been the subject of a great deal of study in recent years. The majority of this study has used simple models, such as node–and–edge graphs, to describe the data. In this paper, we argue that such models, which necessarily limit the structures that can be described and omit temporal information, are insufficient to describe and study OSNs. Instead, we propose that a richer class of Entity Interaction Network models should be adopted. We outline a checklist of features that can help build such a model, and apply it to three popular networks (Twitter, Facebook and YouTube) to highlight important features. We also discuss important considerations for the collection, validation and sharing of OSN data.
social-networks  social-media  network-analysis  networks  research  measurement  methods  twitter  data  social  network 
october 2010 by tsuomela
CASOS brings together computer science, dynamic network analysis and the empirical study of complex socio-technical systems. Computational and social network techniques are combined to develop a better understanding of the fundamental principles of organizing, coordinating, managing and destabilizing systems of intelligent adaptive agents (human and artificial) engaged in real tasks at the team, organizational or social level. Whether the research involves the development of metrics, theories, computer simulations, toolkits, or new data analysis techniques advances in computer science are combined with a deep understanding of the underlying cognitive, social, political, business and policy issues.
complexity  modeling  research  networks  social  analysis  network-analysis  simulation  sociology  agent-based-model  school(CarnegieMellon) 
september 2010 by tsuomela
UCINET is a social network analysis program developed by Steve Borgatti, Martin Everett and Lin Freeman.
software  windows  network-analysis  graphs  social-networking  research  analysis  visualization 
september 2010 by tsuomela
[1008.5166] Network Archaeology: Uncovering Ancient Networks from Present-day Interactions
Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved.
network-analysis  networks  model  mathematics  archaeology  history  influence 
september 2010 by tsuomela
Econometric Measures of Systemic Risk in the Finance and Insurance Sectors
We propose several econometric measures of systemic risk to capture the interconnectedness among the monthly returns of hedge funds, banks, brokers, and insurance companies based on principal components analysis and Granger-causality tests. We find that all four sectors have become highly interrelated over the past decade, increasing the level of systemic risk in the finance and insurance industries. These measures can also identify and quantify financial crisis periods, and seem to contain predictive power for the current financial crisis. Our results suggest that hedge funds can provide early indications of market dislocation, and systemic risk arises from a complex and dynamic network of relationships among hedge funds, banks, insurance companies, and brokers.
economics  complexity  systems  risk  measurement  modeling  interconnection  social-networks  network-analysis  finance 
august 2010 by tsuomela
[1007.3254] Distinguishing Fact from Fiction: Pattern Recognition in Texts Using Complex Networks
We establish concrete mathematical criteria to distinguish between different kinds of written storytelling, fictional and non-fictional. Specifically, we constructed a semantic network from both novels and news stories, with $N$ independent words as vertices or nodes, and edges or links allotted to words occurring within $m$ places of a given vertex; we call $m$ the word distance. We then used measures from complex network theory to distinguish between news and fiction, studying the minimal text length needed as well as the optimized word distance $m$.
semantics  fiction  computer  computer-science  network-analysis  literature  text-analysis 
july 2010 by tsuomela
Researchers Identify Critical 'Bridging' Connectors in Social Networks | News | Communications of the ACM
In order to calculate an individual's bridging, the team systematically deleted each link in the network and calculated the resulting changes in network cohesion. The average change for each person's links is a measure of bridging. A person with two links to members in two different groups when no one else links the groups is a perfect bridge.
social-networks  analysis  network-analysis  community 
june 2010 by tsuomela
[1005.4882] Predicting Influential Users in Online Social Networks
Who are the influential people in an online social network? The answer to this question depends not only on the structure of the network, but also on details of the dynamic processes occurring on it. We classify these processes as conservative and non-conservative. A random walk on a network is an example of a conservative dynamic process, while information spread is non-conservative. The influence models used to rank network nodes can be similarly classified, depending on the dynamic process they implicitly emulate.
network-analysis  influence  leadership  paper  model 
june 2010 by tsuomela
Technology Review: Blogs: arXiv blog: Best Connected Individuals Are Not The Most Influential Spreaders in Social Networks
By contrast, "a less connected person who is strategically placed in the core of the network will have a significant effect that leads to dissemination through a large fraction of the population."
networks  network-analysis  social-networking  social  modeling 
february 2010 by tsuomela
Overview — NetworkX v1.0rc1 documentation
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
programming  python  network-analysis  networks  graphs  libraries  visualization 
december 2009 by tsuomela
Tracing information flow on a global scale using Internet chain-letter data — PNAS
Although information, news, and opinions continuously circulate in the worldwide social network, the actual mechanics of how any single piece of information spreads on a global scale have been a mystery. Here, we trace such information-spreading processes at a person-by-person level using methods to reconstruct the propagation of massively circulated Internet chain letters. We find that rather than fanning out widely, reaching many people in very few steps according to “small-world” principles, the progress of these chain letters proceeds in a narrow but very deep tree-like pattern, continuing for several hundred steps. This suggests a new and more complex picture for the spread of information through a social network. We describe a probabilistic model based on network clustering and asynchronous response times that produces trees with this characteristic structure on social-network data.
information-cascade  information-science  information  communication  email  dissemination  viral  networks  network-analysis  ideas  rumor  internet  circulation  epidemics  diffusion  research  paper  probability  model  social-networks 
august 2009 by tsuomela
Chain letters reveal surprising circulation patterns
Contrary to predictions that large-scale information spreads exponentially, like an explosive epidemic, the researchers found that the letter did not reach a large number of individuals in a few steps. Rather, it took hundreds of steps of people forwarding the e-mail on to reach the 20,000 who signed the found copies.
information-cascade  information-science  information  communication  email  dissemination  viral  networks  network-analysis  ideas  rumor  internet  circulation  epidemics  diffusion 
august 2009 by tsuomela
ACM Ubiquity - In Search of the Real Network Science: An Interview with David Alderson
David Alderson has become a leading advocate for formulating the foundations of network science so that its predictions can be applied to real networks. He is an assistant professor in the Operations Research Department at the Naval Postgraduate School in Monterey, Calif., where he conducts research with military officer-students on the operation, attack, and defense of network infrastructure systems. We interviewed him to find out what is going on.
interview  networks  network-analysis  science  powerlaw  mathematics  graphs  social-networks 
august 2009 by tsuomela
What is the (Next) Message?: Karen Stephenson at OCAD: Organization Beyond Social Networks
She observes – correctly, I think – that most strategic insight and initiative is limited by the fact of ego-centric networks: we know who we know, and only on a very limited basis do we indirectly know those whom our direct network knows.
network-analysis  social-networks 
april 2009 by tsuomela
SSRN-Networks in Finance by Franklin Allen, Ana Babus
Modern financial systems exhibit a high degree of interdependence. There are different possible sources of connections between financial institutions, stemming from both the asset and the liability side of their balance sheet. For instance, banks are directly connected through mutual exposures acquired on the interbank market. Likewise, holding similar portfolios or sharing the same mass of depositors creates indirect linkages between financial institutions. Broadly understood as a collection of nodes and links between nodes, networks can be a useful representation of financial systems.
networks  network-analysis  banking  finance  economics  modeling 
february 2009 by tsuomela
'Six Degrees of Kevin Bacon' game provides clue to efficiency of complex networks
..a study by Marián Boguñá, Dmitri Krioukov, and Kimberly Claffy, published in Nature Physics on November 16, reveals a previously unknown mathematical model called "hidden metric space" that may explain the "small-world phenomenon" and its relationship to both man-made and natural networks such as human language, as well as gene regulation or neural networks that connect neurons to organs and muscles within our bodies.
mathematics  small-world  network-analysis  metric-space 
december 2008 by tsuomela
Modeling the Small-World Phenomenon with Local Network Flow
We introduce an improved hybrid model that combines a global graph (a random power law graph) with a local graph (a graph with high local connectivity defined by network flow). We present an efficient algorithm that extracts a local graph from a given rea
network-analysis  network  small-world  algorithms  complexity 
december 2007 by tsuomela
ATA ~ Advanced Technology Assessment
Italian consulting company that examines networks.
network-analysis  graphs  career 
january 2006 by tsuomela

Copy this bookmark:

to read