Network visualization links: social data and correlation filtering

Network X and Gephi – Gilad Lotan (video)

…In this session I’ll show ways in which we use the python networkx library along with the open source gephi visualization tool to make sense of social network data. We’ll take a few examples from Twitter, look at how a hashtag spreads through the network, and then analyze the connections between users posting to the hashtag. We’ll be constructing graphs, running stats on them and then visualizing…

A tool for filtering information in complex systems

…a technique to filter out complex data sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation-based graphs, giving filtered graphs that preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal…

Spread of risk across financial markets: better to invest in the peripheries (H/T Carl Carrie)

…by extracting the dependency structure of financial equities, a network approach can be used to build a well-diversified portfolio that effectively reduces investment risk. We find that investments in stocks that occupy peripheral, poorly connected regions in financial filtered networks, namely Minimum Spanning Trees and Planar Maximally Filtered Graphs…

Network Metrics, Planar Graphs, and Software Tools

…The connected components tell us what set of pages can be reached from any other just by surfing (no ‘jumping’ around by typing in a URL or using a search engine)… if the largest component encompasses a significant fraction of the graph, it is called the giant component…

Interested in social data? Be sure to check out our new book Intro to Social Data for Traders by our very own Thomas Pendergrass.

Lead image licensed under CC-SA 3.0 from JB

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