Michele Coscia

Another NetSci edition went by, as interconnected as ever. This year we got to enjoy Northeast Asia, a new scenario for us network scientists, and an appropriate one: many new faces popped up both among speakers and attendees. Seoul was definitely what NetSci needed at this time. I want to spend just a few words about what impressed me the most during this trip — well, second most after what Koreans did with their pizzas: that is unbeatable. Let’s go chronologically, starting with the satellites.

You all know I was co-organizing the one on Networks of networks (you didn’t? Then scroll down a bit and get informed!). I am pleased with how things went: the talks we gathered this year were most excellent. Space constraints don’t allow me to give everyone the attention they deserve, but I want to mention two. First is Yong-Yeol Ahn, who was the star of this year. He gave four talks at the conference — provided I haven’t miscounted — and his plenary one on the analysis of the Linkedin graph was just breathtaking. At Netonets, he talked about the internal belief network each one of us carries in her own brain, and its relationship with how macro societal behaviors arise in social networks. An original take on networks of networks, and one that spurred the idea: how much are the inner workings of one’s belief network affected by the metabolic and the bio-connectome networks of one own body? Should we study networks of networks of networks? Second, Nitesh Chawla showed us how high order networks unveil real relationships among nodes. The same node can behave like it is many different ones, depending on which of its connections we are considering.

Besides the most awesome networks of networks satellite, other ones caught my attention. Again, space is my tyrant here, so I get to award just one slot, and I would like to give it to Hyejin Youn. Her satellite was on the evolution of technological networks. She does amazing things tracking how the patent network evolved from the depths of 1800 until now. The idea is to find viable innovation paths, and to predict which fields will have the largest impact in the future.

When it comes to the plenary sessions, I think Yang-Yu Liu stole the spotlight with a flashy presentation about the microcosmos everybody carries in their guts. The analysis of the human microbiome is a very hot topic right now, and it pleases me to know that there is somebody working on a network perspective of it. Besides scientific merits, whoever extensively quotes Minute Earth videos — bonus points for it being the one about poop transplants — has my eternal admiration. I also want to highlight Ginestra Bianconi‘s talk. She has an extraordinary talent in bringing to network science the most cutting edge aspects of physics. Her line of research combining quantum gravity and network geometry is a dream come true for a physics nerd like myself. I always wished to see advanced physics concepts translated into network terms, but I never had the capacity to do so: now I just have to sit back and wait for Ginestra’s next paper.

What about contributed talks? The race for the second best is very tight. The very best was clearly mine on the link between mobility and communication patterns, about which I showed a scaling relationship connecting them (paper – post). I will be magnanimous and spare you all the praises I could sing of it. Enough joking around, let’s move on. Juyong Park gave two fantastic talks on networks and music. This was a nice breath of fresh air for digital humanities: this NetSci edition was orphan of the great satellite chaired by Max Schich. Juyong showed how to navigate through collaboration networks on classical music CDs, and through judge biases in music competitions. By the way, Max dominated — as expected — the lighting talk session, showing some new products coming from his digital humanities landmark published last year in Science.  Tomomi Kito was also great: she borrowed the tools of economic complexity and shifted her focus from the macro analysis of countries to the micro analysis of networks of multinational corporations. A final mention goes to Roberta Sinatra. Her talk was about her struggle into making PhD committees recognize that what she is doing is actually physics. It resonates with my personal experience, trying to convince hiring committees that what I’m doing is actually computer science. Maybe we should all give up the struggle and just create a network science department.

And so we get to the last treat of the conference: the Erdos-Renyi prize, awarded to the most excellent network researcher under the age of 40. This year it went to Aaron Clauset, and this pleases me for several reasons. First, because Aaron is awesome, and he deserves it. Second, because he is the first computer scientist who is awarded the prize, and this just gives me hope that our work too is getting recognized by the network gurus. His talk was fantastic on two accounts.

For starters, he presented his brand new Index of Complex Networks. The interface is pretty clunky, especially on my Ubuntu Firefox, but that does not hinder the usefulness of such an instrument. With his collaborators, Aaron collected the most important papers in the network literature, trying to find a link to a publicly available network. If they were successful, that link went in the index, along with some metadata about the network. This is going to be a prime resource for network scientists, both for starting new projects and for the sorely needed task of replicating previous results.

Replication is the core of the second reason I loved Aaron’s talk. Once he collected all these networks, for fun he took a jab at some of the dogmas of networks science. The main one everybody knows is: “Power-laws are everywhere”. You can see where this is going: the impertinent Colorado University boy showed that yes, power-laws are very common… among the 5-10% of networks in which it is possible to find them. Not so much “everywhere” any more, huh? This was especially irreverent given that not so long before Stefan Thurner gave a very nice plenary talk featuring a carousel of power laws. I’m not picking sides on the debate — I feel hardly qualified in doing so. I just think that questioning dearly held results is always a good thing, to avoid fooling ourselves into believing we’ve reached an objective truth.

Among the non-scientific merits of the conference, I talked with Vinko Zlatic about the Croatian government on the brink of collapse, spread the search for a new network scientist by the Center for International Development, and discovered that Korean pizzas are topped with almonds (you didn’t really think I was going to let slip that pizza reference at the beginning of the post, did you?). And now I made myself sad: I wish there was another NetSci right away, to shove my brain down into another blender of awesomeness.  Oh well, there are going to be plenty of occasions to do so. See you maybe in Dubrovnik, Tel-Aviv or Indianapolis?

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As I wrote previously, this year I missed NetSci, the yearly appointment for everybody who is interested in network analysis. The reason is that I was invited to give a talk at the Collective Intelligence conference, which happened almost at the same time. And once I got an invitation from Lada Adamic, I knew I couldn’t say no to her. Look at the things she did and is doing: she is a superstar scientist! So I packed my bags and went to the West Coast.

The first day was immediately a blast. Jeff Howe chaired the first session with some great insights about crowdsourcing. As you know, crowdsourcing is a super hip thing nowadays. It goes like this: individually, each one of us is pretty terrible at solving a hard problem. But if we put together enough terrible people, the average of their errors cancels out and we get an almost perfect performance. The term itself crowdsourcing was basically invented by Jeff (and Mark Robinson) when he was writing for Wired. The speakers in Jeff’s session showed us some cool examples of crowdsourcing research. The one that stuck with me the most was from Ágnes Horvát: she and her co-authors were able to analyze the internal communications of a hedge fund about investments and use the features of this communication (frequency of messages, mood, etc) to predict how the investments would perform. And they got it right much more than the strategists at the hedge fund itself.

The second day started with the session with my talk in it. A talk about memes of course! The people I got lined up with were spectacular. Jacob Foster talked about the collective intelligence of science. How do scientists make sense of the incredible amount of research out there? And how is it possible to advance knowledge in such hard times, when there are tens of new studies published every day? Dean Eckles gave an insightful talk about how Facebook users react when their stories get “snoped” (Snopes is a website dedicated to debunk hoaxes). Finally, fellow Italian Walter Quattrociocchi also spoke about hoaxes on Facebook: how they spread, how conspiracy believers interact with skeptics, and so on.

In the next session I attended, I particularly liked two talks. First, Ben Green talked about collective intelligence, and what it actually is. It reminded me of community discovery in networks: scientists dove enthusiastically into it, producing hundreds of papers. However, many didn’t realize that “communities” (and “collective intelligence”) are not so easily defined. Green is trying to fix that. Richard Mann‘s talk was also very interesting: in his work with Dirk Helbing he designed incentive strategies for getting the best out of the wisdom of crowds.

The lunch keynote was from a superstar in collective intelligence: Regina Dugan. Just to give you an idea about her, her CV sports a position as program manager at DARPA and she currently is vice president of Engineering, Advanced Technology and Projects at Google. Not bad. She shared her experiences in directing and experiencing the process of doing cutting edge research. Her talk was a textbook example of motivational speaking for scientists and entrepreneurs alike.

Finally, I had the pleasure to attend a couple of talks about prediction markets. These communities are basically a stock market for opinions. Given an event, say the 2016 president elections, people can put money on their prediction of who is going to be the winner. Websites like SciCast put in place some rules about buying and selling opinion “stocks” and eventually the market price converges on people’s best estimate of every candidate’s odds to win. Prediction markets are a favorite of Nate Silver, and he talks quite a lot about them in “The Signal and the Noise”.

Unfortunately, my report of the conference ends abruptly here, as I had to miss the last day of conference. But the experience was well worth the trip, and I am very grateful for the invitation to Lada Adamic, Scott Page and Deborah Gordon. Unfortunately, this also means that I discovered a shiny event that overlaps with NetSci. Next year, I’ll have to face hard decisions when I allocate my conference time in early June.

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NetSci, the top global conference about network science, never fails to be a tornado of ideas. Now that the dust has settled, I feel a bit easier to put this year’s thoughts on this post. Yes, this is yet another conference report by yours truly.

Let’s first get over the mandatory part of the report: an evaluation of the awesomeness of the Multiple Networks satellite I co-organized with my friends scattered around Europe. As said, this year’s edition was open to submissions and we received 17 of them. I think that, as a start, that is a good figure. Also, the attendance was more than satisfactory, and it appears scattered only because we got the largest room of the conference! Here’s proof!

The overall event was a great success. The talks were very interesting and we had a great unexpected bonus point. One of our keynotes, as you might remember, was Mason Porter. Well, the guy actually got the Erdos-Renyi prize this year! The Erdos-Renyi prize has been established in 2012 and it goes to outstanding young researchers in network science. Well, make a note of this: speaking at the Multiple Networks satellite will eventually get you some important awards. After all, everybody knows that correlation = causation.

My favorite satellite (besides the one I organized, obviously) continues to be the Arts, Humanities and Complex Networks symposium. This year it was a little bit tougher than usual, with a lot of qualitative stuff that not everybody can appreciate. However, their keynote by Lada Adamic was nothing short of outstanding. She is currently working at Facebook, a position that gives her a privileged vantage point over memes and viral events. You know that those things tickle my curiosity very strongly, and Lada’s work is really great. She presented her work, where she proves that meme evolution and mutation on Facebook follows very closely the same mechanics of evolution and mutation we find in the biological world. Good news for my old paper, which was heading in the same direction!

Which brings me to the main conference, because one of the best talks I attended was from Jon Kleinberg, who collaborated with Lada on another memes-meet-Facebook work. In that case, there is less good news for me. My research plan is to use meme content to predict virality. However, the Kleinberg-Adamic dream team showed that content is actually a very weak factor! (Here’s a blog post about it).

There is still hope, though. My way to deal with content is fundamentally different than theirs. Plus the problem they are studying is slightly different from mine: they are analyzing memes that are already going viral and they want to know how popular they will get. I’m more focused on knowing if the meme is going to be popular at all, and I’m not that concerned about whether everybody will know it or only a niche group.

Virality of content was a very hot topic this year, because there were two other fantastic talks about it. One was by Sinan Aral, and he talked about how much we are influenced by a post’s popularity when we read it. Controlling for content (and believe me when I say that Sinan is one of the best experiment designers out there), if we know that a post is popular we are more likely to upvote it. This is so true that Reddit itself decided, for some subreddits, to hide the post score for the first few hours, so that real good content will eventually flow to the top once the discussion is settled.

On top of that, also James Gleeson talked about a theoretical model that can account for the popularity distribution of memes. The model sounds simple. You just assume that a person has a box containing all the memes they saw in the past. With some probability, the person will either come up with something new or reshare a meme from their box. When resharing from the box, there is a memory effect for which more recent memes are more likely to be reshared. Whenever you share something, regardless if it is new or not, it ends up in your friend’s boxes. Even if it looks so simple, the actual solution of the model isn’t it at all and James is so good he defies belief. And, at the end of the day, everything works like a charm. Again, this does not bother me too much, because it only predicts the distribution of popularity, not which memes are going to be popular, a different problem.

Besides all this work meme popularity, there were other very interesting talks. I mention:

• The very elegant talk by Chris Moore on community discovery, which also has the by-product of providing witty one liners for many occasions (for example “Physicists like to minimize functions because, you know, rocks fall”);
• The nice talk by Frank Schweitzer on the role of active individuals in collaboration networks, who have the side effect of making the networks more unstable and prone to breaking apart (damn you, hyper-active people!);
• The usual fun of the lighting talks (they could not call them ignite talks because of copyright issues). My favorite for this year was from Max Schich, with a really great panorama of the art market in London, Paris and Amsterdam from the Getty dataset. Aaron Clauset and Roberta Sinatra deserve to be mentioned too, with two great talks about climbing the greasy pole in academia (is it really worth it to shoot for big name universities? Short answer: no).

That’s it! You can see that also this year there was a lot to see and to think about. I am already looking forward for next year!

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