The Walk of Pi: In 736036 Days Digits Around the World

Happy $pi$ day everyone! But it is not just an ordinary $pi$ day, no, it is the ultimate $pi$ day!

3/14/15 9:26:53
To celebrate this awesome day, i decided to write an entry devoted to the beauty of $pi$. Specifically, about the random walk of $pi$.

 

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Soccer Analytics Part 2: Why Al Kuwait SC was (probably not) the Best Team in 2013

In the first part of my Soccer Analytics series, I talked about general statistics of my dataset of the season 2013. As a reminder, i scraped all results from 177 domestic leagues and intra continental cups world wide. This entry will deal with the question “Who was the best team in 2013?” according to network analysis and why the result is (most likely) wrong.

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Not Interesting Networks: The Human Body

“Networks are everywhere” is THE catch phrase of social network analysis. As I said in a previous post, if you are a network scientist everything looks like a network to you.  That’s why I decided to start a series about “everywhere” networks. But not just any. No! In particular those that are just not interesting at all. Although networks might be ubiquitous, that does not always make them worthwhile studying.

With this special kind of networks, I will just do some fancy visualizations and maybe some boring statistical analysis. To emphasize the non-scientific relevance, the visualizations and statistics will be presented with the dearly beloved comic sans.


Body Part Relationships Network

I got the data from here. The description of the data is as follows:

“[…] contributors classified if certain body parts were part of other parts. Questions were phrased like so: “[Part 1] is a part of [part 2],” or, by way of example, “Nose is a part of spine” or “Ear is a part of head.”

Well if that’s not exciting…

Here is a visualization of the network

A cluster analysis revealed, to which class of body parts (upper in light blue, lower in light red) certain body parts belong. The algorithm was not so sure about the belly though.

The following table shows the most important body parts according to some centrality measures and what these measures could stand for.

So the head is the most important body part and the face is full of other things. Good to know.

Putting the Sex in SNA: Hook up Networks

Imagine you are a network scientist meeting new people in a bar. At one point, there is always the question: “So what is your research topic?”. Shocked and horrified, you are looking for an answer that does not scare away your new acquaintance. “algorithmic graph theory”? Sounds to nerdy. “social network analysis” ? Sounds better but you are tired of explaining that this is not the same as browsing facebook all day. Maybe an example from your work! “Protein Interaction Networks”? Oh god i had too many beers to explain that.

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Friends and Hypergraphs: The One With All The Networks

Undoubtedly, Friends is one of my favorite tv series. I guess i am not the only one there, since the hosting of all episodes on netflix created quite a stir in the online community. The story of the show is quite easy to follow: Ross loves Rachel, Ross dates Rachel, Rachel breaks up with Ross, Rachel loves Ross, Ross marries Rachel, Ross divorces Rachel, Ross loves Rachel, Ross and Rachel have a happy end. Oh yeah between all the Rachel Ross dilemmas, Monica marries Chandler, Phoebe sings smelly cat and Joey does all kinds of shenanigans. So the question is, is the “Ross and Rachel” story the most central element of the show?
To answer this question, I am gonna look at a dataset of shared plotlines throughout the whole show. That is, which subset of the six characters appeared  together in in a plot during an episode. These plots can range from simply hanging out together in Central Perk to some hanky-panky in the bedroom. We can see a shared plotline as some form of interaction and therefore analyse the show from a network perspective. Great! That is my area of expertise! However, what renders the analysis a bit more complicated is the fact, that plotlines can consist of more than two characters, creating a link with more than two endpoints. So we are not just dealing with a regular network, but with a hypergraph.

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