Reddit reviews Networks: An Introduction
We found 5 Reddit comments about Networks: An Introduction. Here are the top ones, ranked by their Reddit score.
Oxford University Press USA
We found 5 Reddit comments about Networks: An Introduction. Here are the top ones, ranked by their Reddit score.
The social branch of network science studies this kind of thing and would have some good uses for the data set, I'm sure.
http://scholar.google.com/scholar?hl=en&q=social+contact+network&btnG=&as_sdt=1%2C5&as_sdtp=
http://barabasilab.com/pubs-socialnets.php
http://barabasilab.com/pubs-humandynamics.php
http://www-personal.umich.edu/~mejn/pubs.html
With respect to looking for happiness, you might look for studies on sentiment analysis and the spreading of emotion in social networks. I know people have looked at how positive and negative emotion traverses the graph of twitter followers and retweets.
There's a small lifetime's worth of reading in those links. If you want a fairly comprehensive introduction that balances well between theory and examples, check out Mark Newman's book.
For the type of graph (network) theory that is currently hot in neuroscience contexts, [Newman's book](http://www.amazon.com/Networks-An-Introduction-Mark-Newman/dp/0199206651
) is a great compendium (quite readable, but fairly comprehensive).
For bedside reading about mammalian cortical networks in particular, Networks of the Brain and Discovering the Human Connectome, both by Olaf Sporns, are well worth a look.
From there... it's already becoming a pretty big literature. If you have some specific areas of interest, I can do my best to point you to resources. Take my suggestions with a grain of salt, though... I'm a pure mathematician who kinda got seduced into applied maths... which means I probably don't know as much about either discipline as I should.
Well, as an IR scholar that applies inferential network methods to substantive IR questions, I think the previous findings show promise for a thriving research agenda. Send me a PM if you'd like to talk about anything in particular. If you're looking for IR-substantive references, here are some favorites:
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1287857
https://www.dropbox.com/s/fwzlmae58fx1fax/Cranmer-CV.pdf?dl=0
http://ps.ucdavis.edu/people/maoz/MaozCV.pdf
For networks specific texts, it depends on what level you're at. I'd recommend Wasserman and Faust as a foundation:
https://www.amazon.com/Social-Network-Analysis-Applications-Structural/dp/0521387078
But this is also a favorite:
https://www.amazon.com/Networks-Introduction-Mark-Newman/dp/0199206651/ref=sr_1_1?s=books&ie=UTF8&qid=1475112947&sr=1-1&keywords=newman+networks
From that, I'd recommend reading this:
http://onlinelibrary.wiley.com/doi/10.1111/ajps.12263/abstract
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MacKay: Information theory, inference and learning algorithms and Newman: Networks for the latter.