Social Network Analysis
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Social Network Analysis
Social Network Analysis - Un espacio para compartir herramietas, experiencias, investigaciones hacer de SNA y su aplicabilidad.
Curated by Pablo Torres
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Twitter Audience Profiling - OU/BBC Feynman Challenger Co-Pro

Twitter Audience Profiling - OU/BBC Feynman Challenger Co-Pro | Social Network Analysis | Scoop.it
Another strong piece of TV commissioning via the Open University Open Media Unit (OMU) aired this week in the guide of The Challenger, a drama documentary telling the tale of Richard Feynman's role...

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Datavisualization.ch Selected Tools

Datavisualization.ch Selected Tools | Social Network Analysis | Scoop.it
Datavisualization.ch Selected Tools is a collection of tools that we, the people behind Datavisualization.ch, work with on a daily basis and recommend warmly.
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Redes sociales lineamientos_basicos

Presentación de clase utilizada para tratar el tema de las redes sociales y el análisis de redes sociales como método en Psicología Social Comunitaria.

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Learning Analytics

Learning AnalyticsHBO-masteropleidingAlberdingk Thijm College, Hilversum, NL, 12 March 2013Erik Duvalhttp://erikduval.wordpress.com@ErikDuval

Via Paulo Simões, juandoming, ThePinkSalmon
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Raquel Oliveira's curator insight, March 19, 2013 12:22 PM

Great ideas about how many posibilities we have to follow how much learning the audience is taking.

Jorge Forero's curator insight, March 20, 2013 12:15 AM

Aprendiendo analytics | visita nuestro blog sobre estrategia digital: http://www.dweb3d.com/blog/estrategia-digital-marketing-y-posicionamiento-seo.html

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Brand Monitoring in Social Web

Charla a cargo de Francesc Gómez Morales sobre la monitorización de una marca en los medios sociales a través de herramientas como Radian6 o Brandchats.

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Capacitaciones BI: Social Network Analysis, una mirada de negocios

Capacitaciones BI: Social Network Analysis, una mirada de negocios | Social Network Analysis | Scoop.it
Las técnicas de Social Network Analysis (SNA) están siendo cada vez mas utilizadas por empresas privadas y organismos públicos para estudiar el comportamiento que poseen las personas al relacionarse, y así facilitarles el acceso a ...
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Networks, Crowds, and Markets: A Book by David Easley and Jon Kleinberg

Pablo Torres's insight:

Networks, Crowds, and Markets combines different scientific perspectives in its approach to understanding networks and behavior. Drawing on ideas from economics, sociology, computing and information science, and applied mathematics, it describes the emerging field of study that is growing at the interface of all these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

 

The book is based on an inter-disciplinary course entitled Networks that we teach at Cornell. The book, like the course, is designed at the introductory undergraduate level with no formal prerequisites. To support deeper explorations, most of the chapters are supplemented with optional advanced sections.

 

The book is published by Cambridge University Press (2010); for more information, please see Cambridge's page for the book.

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PageRank Algorithm Reveals Soccer Teams' Strategies #sna

PageRank Algorithm Reveals Soccer Teams' Strategies #sna | Social Network Analysis | Scoop.it

Using network theory to analyse the performance of soccer teams and players produces unique insights into the strategy of the world's best team.


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Tony Brugman (Bright & Company)'s curator insight, February 26, 2013 2:46 PM

Beautiful visualization based on (Social) Network Analysis giving more insight behind the success of Spain's 2010 victory over The Netherlands at the World Championship Soccer in South-Africa.

 

"A visual inspection of these networks immediately reveals some interesting insights into the match. The thickness of the arrows represents the number of passes between nodes and it is immediately clear that the Spanish team pass more often. This image captures 417 passes by the Spanish team versus 266 for the Netherlands."


The article continues with giving notions on the aspects of network science (eg. closeness centrality, betweenness centrality) and PageRank algorithm (eg. popularity).

 

It concludes with the limitations/improvements to this approach:

"The data is an average over several games so it fails to capture the dynamics of specific games. And the positions of the nodes are also a vast generalisation and taken only from a player’s nominal starting position."

 

"Perhaps more fascinating would be a way of collecting and analysing the data in real time to produce a network-based analysis of a game as it happens."

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How women organize social networks different from men : Scientific Reports

How women organize social networks different from men : Scientific Reports | Social Network Analysis | Scoop.it
Superpositions of social networks, such as communication, friendship, or trade networks, are called multiplex networks, forming the structural backbone of human societies. Novel datasets now allow quantification and exploration of multiplex networks.

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ukituki's curator insight, February 13, 2013 11:27 PM

On the individual level females perform better economically and are less risk-taking than males. Males reciprocate friendship requests from females faster than vice versa and hesitate to reciprocate hostile actions of females.


On the network level females have more communication partners, who are less connected than partners of males. We find a strong homophily effect for females and higher clustering coefficients of females in trade and attack networks. Cooperative links between males are under-represented, reflecting competition for resources among males.


These results confirm quantitatively that females and males manage their social networks in substantially different ways.

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Social Network Analysis Books Worth Reading

Social Network Analysis Books Worth Reading | Social Network Analysis | Scoop.it
Books from the field of Social Network Analysis
Tab created for FB community page https://www.facebook.com/SocialNetworkAnalysis
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Predictive Analysis: New generation of computational intelligence systems

Predictive Analysis: New generation of computational intelligence systems | Social Network Analysis | Scoop.it
Large parts of our lives are now being monitored and analysed by computers. Log on to Amazon and intelligent data analysis software can recommend a selection of books you might like to read.
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Utilidad e impacto de las redes sociales

Participación en el “FORO DE DESARROLLO SUSTENTABLE CANCÚN 2012", organizado por la Fundación Científica y Cultural Isidro Fabela, Capitulo Quintana Roo AC, en coordinación con la Unidad Nacional de Asociaciones de Ingenieros AC (UNAI)...

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Factores para la adopción de linked data e implantación de la web semántica en bibliotecas, archivos y museos

Factores para la adopción de <em>linked data</em> e implantación de la web semántica en bibliotecas, archivos y museos | Social Network Analysis | Scoop.it
Introducción. Se elabora un marco para identificar el nivel de penetración y madurez de las tecnologías linked data, como una faceta específica del modelo abierto del W3C para la web semántica, en el sector de las bibliotecas, archivos y...

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3 consejos prácticos sobre Web Semántica - Nelson Piedra @nopiedra

Drupal Summit Latino - Loja, Ecuador Nelson Piedra, docente investigador sobre Web Semántica, datos relacionados, bigdata, entre otros.
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Buscadores semanticos Parte 1

Este primer artículo, que forma parte de una serie escrita por Miguel Ángel Abián, se encarga de analizar y explicar los conceptos de búsqueda semántica y buscadores semánticos, tan relacionados con la web semántica.

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Blog - Social Media Marketing

Blog - Social Media Marketing | Social Network Analysis | Scoop.it
Hemos aplicado la técnica del análisis de redes sociales (social network analysis) para conocer cómo se relacionan los diputados tuiteros entre sí. La metodología utilizada podría resumirse de la siguiente manera: 1.
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Science of Winning Soccer: Emergent pattern-forming dynamics in association football

Science of Winning Soccer: Emergent pattern-forming dynamics in association football | Social Network Analysis | Scoop.it

While football (soccer) is alternately known as a sport, a national pastime, or a national obsession, the New England Complex Systems Institute (NECSI) is the first to place soccer in the category of a complex social system. A new study from NECSI uses quantitative analysis to reveal the key team dynamics within a Premier League match.

 

L. Vilar, D. Araújo, K. Davids, Y. Bar-Yam, Science of Winning Soccer: Emergent pattern-forming dynamics in association football. Journal of Systems Science and Complexity (in press).


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Social Network Analysis Labs in R and SoNIA

SoNIA is a Java-based package for visualizing dynamic or longitudinal "network" data

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SoNIA is a Java-based package for visualizing dynamic or longitudinal "network" data

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#ChaosIsGood: Using Social Networking Analysis To Measure Influence

#ChaosIsGood: Using Social Networking Analysis To Measure Influence | Social Network Analysis | Scoop.it

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HR Trend Institute's curator insight, February 9, 2013 8:18 AM

Chaos is good! 

Andries Du Plessis's comment, February 27, 2013 3:58 PM
Once we understand where the influencers are in a network we can start to undertand how to manage them, right? Im surely curious to understand the new cohort of students' networks
luiy's curator insight, March 14, 2013 4:31 PM

Centrality 

Often, regardless of the industry or organization performing social networking analysis, it is important to understand which models govern their specific target network. It is also critical to understand the smaller, local relationships between the actors (nodes). For example, for intelligence analysis purposes, it is critical to identify how information flows through the network and which nodes are the most active in collecting or sharing information. As such, a centrality of a network describes how important/influential a node is to a network.

 

 Highly central networks operate similar to highly centralized governments such as theocracies or monarchies while least centralized networks mimic democratic system of governments. The centralization of a network is approximately an average of the maximum centrality of a single node over the entire network and can be calculated by Freeman’s general formula.  For practical purposes, it is not always required to calculate this number to be able to realize the centrality of a network. For example, comparing today’s terrorist groups to traditional ones it can be observed without going through the calculations that today’s groups are much less centralized and hence harder to target. Low centralized networks, though sometimes not as effective in terms of governance and implementation of an overall strategy, are much more resilient (‘anti-fragile’) to shocks. For example, it’s much easier to contain a virus in a highly centralized network than it is in a low centralized network. The other concepts of centrality: ‘Closeness’ and ‘Betweenness’ attempt to measure the minimum number of nodes information or a meme would have to travel to get from one node to another. A very close network with many well-connected nodes (‘Betweenness’) would be much better and faster in communicating certain information, virus, knowledge, tradition, and meme across its entire network. A network with a very low ‘Closeness’ would hence be less effective and efficient in doing the same. 

Influence 

One of the most important outcomes of SNA is determining influencers across a network, as well as their level of influence. There are various ways to locate influencers such as number of followers, friends or connections as well as level of activity on social media. However more models are needed to better locate influencers. 
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Social Network Analysis, a Ph.D. level course

Social Network Analysis, a Ph.D. level course | Social Network Analysis | Scoop.it

Social Network Analysis, a Ph.D. level course taught each Spring by Steve Borgatti under the auspices of the University of Kentucky LINKS Center


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