Tag Archives: networks

Network Stats Continue

A couple of new papers on networks crossed my desk this week.   Well, more than a couple, since I’m PC-ing for the Web Algorithms Workshop (WAW) right now.  But a couple crossed my desk that I’m not reviewing, which means I can write about them.

Brendan Nyhan writes:

Just came across your blog post on Christakis/Fowler and the various critiques – thought this paper I just posted to arXiv with Hans Noel might also be of interest: The “Unfriending” Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence

Unfriending is interesting, and an area that seems understudied.  In online social networks, there is often no cost to keep a tie in place.  The XBox Live friend network is not such a case: an XBox gamer sees frequent updates about their friends’ activities. That’s why I thought it made sense when I learned that the XBox Live social network does not exhibit the heavy tailed degree-distribution phenomenon that has been widely reported in real-world networks. Someone should talk Microsoft into releasing an anonymized edition of this graph (if such an anonymization is possible…).

Meanwhile, Anton Westveld and Peter Hoff’s paper on modeling longitudinal network data caught my eye on arxiv: A Mixed Effects Model for Longitudinal Relational and Network Data, with Applications to International Trade and Conflict.

All the things I’d like to read… I could write a book about it. Before I even had time to finish writing this post, I saw another one: On the Existence of the MLE for a Directed Random Graph Network Model with Reciprocation.

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Filed under statistics

Societally-useful applications of Networks

Aravind Srinivasan writes:

I am teaching a new grad course on Networks in the Fall, and would like to include some societally-useful applications of networks as possible projects for the students (can be theory, very applied, or anywhere in the middle); these would be among a menu of choices available to the students. Could you please let me know if you have any suggestions? Of course, I will be happy to suggest anything useful that came out of my course, if you are interested.

I am interested, and it’s a fun/important thing to think about the societal value of your work periodically (not that I get to work on networks very much these days). I’ll put my response “below the fold”, in case you want to come up with your own list first. Continue reading

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Network Theory in Health Metrics

The heavy-tailed/small-worlds crowd had a big impact in health research recently, and now it’s drawing criticism from the theorists. Slate covered the story well a couple weeks ago, and interviewed Russ Lyons at length about the methodological shortcomings of the evidence that obesity, smoking, and loneliness are socially contagious. The Slate article even links to Russ’s preprint on the matter, which is some pretty technical stuff to point a general audience towards. Go Slate!

When I passed on some of Russ’s concerns to my experienced health metrics colleagues, one replied that the idea of social contagion is important enough that it doesn’t matter if the methods are wrong. Interesting perspective. It reminds me of Gian Carlo Rota’s ordering of mathematical results: most important are definitions, less important that that are theorems, and much, much less important than that are the proofs.

I’ve been in meetings for almost 3 weeks now, and meanwhile more good papers on networks for health are pouring out. Christakis and Fowler have posted a preprint to arxiv, showing how network thinking improved flu surveillance of Harvard undergrads. So maybe the idea was the important part. Meanwhile, the Cosma Shalizi and Andrew Thomas have an additional critique preprint, to be put in the same category as Russ’s. I asked Russ what he would accept as evidence of social contagion, and I didn’t find out, but the paper by Shalizi and Thomas says maybe nothing can be convincing: Homophily and Contagion Are Generically Confounded in Observational Social Network Studies.

For me, it’s time to get back to that meeting!

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Filed under global health, statistics