The Difference Between Funny and LOL
21–30 of 56 posts
Re: The Difference Between Funny and LOL
#22Le sigh. All of the comments are on the UX of the site, and not the content of the article. Come on guys. This article was really interesting to me (though obviously he doesn't get terribly into depth). I find data vis like this, whether it be super meaningful or not to be really cool. I'd like to see more analysis like this done with it.
To be honest, I'm fine with this kind of submission, I think it's a better way to see a product in context than a "Show HN", however, some people may see it as being underhanded as it defies the convention around here.
Re: The Difference Between Funny and LOL
#23I worked on a project with a guy who did network analysis like this. It was pretty cool... the first three times. After that it seemed like every problem had to involve a whizbang graphic - then I realized he didn't actually know how to program at all. His whole job was 'analysis', which was using Tableau and a graph partitioning program to produce visualizations (pretty much using the defaults), and then try to expl…
Re: The Difference Between Funny and LOL
#24Re: The Difference Between Funny and LOL
#25What software was used to make those graphs? Or did I tap through it
Re: The Difference Between Funny and LOL
#26Le sigh. All of the comments are on the UX of the site, and not the content of the article. Come on guys. This article was really interesting to me (though obviously he doesn't get terribly into depth). I find data vis like this, whether it be super meaningful or not to be really cool. I'd like to see more analysis like this done with it.
Re: The Difference Between Funny and LOL
#27Modularity is one measure of the structure of networks or graphs. It was designed to measure the strength of division of a network into modules (also called groups, clusters or communities). Networks with high modularity have dense connections between the nodes within modules but sparse connections between nodes in different modules. Modularity is often used in optimization methods for detecting community structure in networks. However, it has been shown that modularity suffers a resolution limit and, therefore, it is unable to detect small communities. Biological networks, including animal brains, exhibit a high degree of modularity. A 2013 paper shows that modularity in biological networks may have evolved due to selection pressures to reduce connection costs.
Paper on Modularity Maximization algo to identify communities in graph is at http://www-scf.usc.edu/~gaurava/modularity.pdf
There are many other ways to cluster the graph.
Re: The Difference Between Funny and LOL
#28Re: The Difference Between Funny and LOL
#29Is the Japanese Python community really that big? What do they use it for?