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What makes a meme— an idea, a phrase, an image—go viral? Researchers, by mining public Twitter data, have found that a meme's “virality” is often evident from the start.
Social network analysis and mining of the social web, to investigate spreading of ideas, information, viruses. Now we've got all the tools. So just do it and have some fun!
Are you sure you want to delete this scoop?
Some important ideas here for people interested in change.
Forecasting the Future Twitter Trends in hashtags
Twitter, what happens when things go viral?
This post was originally featured on published on May 6th, 2010. Since the website will be relaunched and the post removed, I have relocated the tutorial to my personal page so that the Gephi commu...
A "classic" operative introduction to Social Network Analysis and to Gephi: we all started from that! Just play around!
Since the release of Mining the Social Web, 2E in late October of last year, I have mostly focused on creating supplemental content that focused on Twitter data. This seemed like a natural starting...
Terrific work out here! Mining the Social Web is still growing, taking its readers to know advanced tool and techniques in Data Mining and Social Network Analysis! Stay tuned...I suspect more and more is coming!
Evidence is Power
Feels like a nice and complete tutorial! I'm definitely taking a closer look to ScraperWiki, but I'd like to be able to do the analysis in R/Python...maybe one day!
Tutorial to harvest tweets from Twitter using ScraperWiki and how to analyse them using social network analysis and Gephi.
We are launching a series of posts to teach the basics of graph visualization, written by Sébastien Heymann in collaboration with Bénédicte Le Grand of Université de Paris 1. At Linkurious we are working on better software to help people visualize graphs easily. Of course writing software is a powerful way to improve our ability …
Graph and network visualization with open tools, such as Gephi and Neo4j! Looks great!
Mining for Network Data and Content Analysis
An impressive sidebar, full of #sna resources & tool ! Nice discovery!
The way information spreads through society has been the focus of intense study in recent years. This work has thrown up…
A different view on information spread and diffusion on a network. A simple model, accounting for the key difference between "viruses" and "information", both from the sender and the receiver point of view.
The way information spreads through society has been the focus of intense study in recent years. This work has thrown up some dramatic results; it explains why some ideas become viral while others do not, why certain individuals are more influential than others and how best to exploit the properties of a network to spread information most effectively.
But today, Chuang Liu at Hangzhou Normal University in China and a few pals have a surprise. They say that when information spreads, there are always blind spots in a network that never receive it. And these unreachable dark corners of the network can be numerous and sizeable.
Until now theorists have predicted that information can always spread until it saturates a network to the point where everybody has received it. These predictions are come from models based on our understanding of diseases and the way they percolate through a population. The basic assumption is that information spreads in the same way.
Cytoscape Official Web Site
Definitely the next tool in my "closely look at" list...
Use social network centrality measures, like degree, betweenness and closeness centrality, and kCores, Distance and Shortest path in your network visualization
Maybe worth a closer look...
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"[...] “Twelve Degrees of Separation” is not quite as catchy as six, but it's still impressive that any two athletes who played for any of 6,000 teams over 140 years can be covered in just a dozen steps [...]"
What can a more-than-60-year-old book tell us about Twitter and Facebook?
...another worth reading book?!
Richard Price's Academia.edu has grown exponentially to 4.8 million academic users, many of whom return each month. A former professor writes about its potential.
I'm not quite sure of the advantages of this social network to the scientific/academia community, but a couple of hints about business in general are quite embraceable, namely "Deal directly with customers and give them lots of additional stuff to buy when they become your customer" and "If it is easy and fun, people will use it"!
People connect to form groups on Twitter for a variety of purposes. The networks they create have identifiable contours that are shaped by the topic being discussed, the information and influencers driving the conversation, and the social network structures of the participants.
A deep analysis of Twitter crowds and conversations, from their building blocks! Interesting!
Introductory materials, handouts and R scripts for network analysis and visualization.
Wow! Every tool you want for Social Network Analysis! Maybe I'll be posting all of them separately, with some notes!
ICWSM 2011 Tutorial Sebastien Heymann and Julian Bilcke Gephi is an interactive visualization and exploration software for all kinds of networks and relation...
Not just the same-old-story tutorial! A lot of call-to-action inside! Have fun!
Online conversations (and even offline ones) are, deep down, networks. But how to visualize network data so that they make sense to non-network scientists? Pres
As the title suggests...interesting approach! The analysis is clear...I just wonder "how can this be of any help"?
Worth a complete reading! A little bit technical, but if you are interested in doing that, you can't dodge the math!
Just can't help waiting!
Since its first formulations almost a century ago, mathematical models for disease spreading contributed to understand, evaluate and control the epidemic processes [...] In this review, we will introduce the basic concepts of epidemiology, epidemic modeling and networks, to finally provide a brief description of the most relevant results in the field.
Epidemics on social networksMarcelo N. Kuperman
Basics of SIS/SIR models of spreading epidemics, and their relations to social networks.
A good review about epidemic models in social networks, SIS, SIR, etc ...
Transforming Curiosity into Insight
A blog, a journey, a challenge. Let's get started!
Facebook can isolate your spouse or partner based on your network of friends.
This is SNA, indeed. I'll definitely have that paper read.
Social Network Analysis is a free online class taught by Lada Adamic of University of Michigan (Social Network Analysis | @scoopit http://t.co/YGKYi2FXTZ)...
I can't recommend this online course strongly enough! You'll learn fundamentals of Social Network Analysis, how to use Gephi for network visualization and to understand basic social mechanisms (such as virus spread) with Netlogo. Clear and challenging offer by Lada Adamic and University of Michigan.
What is the connection between Social Networks and Being Lonely? Inspired and Based on the wonderful book by Sherry Turkle - Alone Together. Script, Design &...
Interesting reflections...I'll definitely give a shot to the book "Alone together" by Sherry Turkle!