Mexican politics in the social space

What does the relationship between political parties look like in Mexico when it comes to online audiences? We wanted to answer this question, therefore we took to analyzing the Facebook activities of various fanpages for the month of January – just like we did earlier this month with Colombian online politics.

The analysis looked into the online dynamics between and amongst the registered political parties in Mexico. Only fanpages were considered, user or group accounts on Facebook were ignored.
 

The examined data covered:

• 12 356 posts;
• 239 884 users who liked posts;
• 18 972 users who commented on posts.

In order to reveal the dynamics amongst and between political parties, we have included the aggregate network of parties indicating the structure of their overlapping audiences, the timeline exposing the activity of their supporters, and a cross-over audience analysis for each analyzed political page.


Click here to download the full January Facebook analysis of Mexican political parties.

Our Colombian online politics analysis made the front page of La Republica

What is the relationship between political parties in Colombia in terms of online audience?
This was the first and foremost question of our mini-research.

Our analysis looked into the dynamics of online political audiences in Colombia by examining the January 2014 activities of 118 Facebook fanpages of various political parties. The aim was not to provide a representative analysis, similar to that of the offline polls, but to offer a glimpse into of the different supporters of these parties.

We've only considered fanpages in the study and ignored user or group accounts. The examined data covered 5 835 posts, 60 067 users who liked posts and 4 947 users who commented on posts.

The analysis includes the aggregate network of parties revealing the hidden structures of online supporters between them; the timeline of parties indicating the activity of their supporters; and a cross-over audience analysis for each analyzed political page.

Click here to download the full Colombian online politics analysis.

The first autonomous drones that flock like birds are Hungarian!

Our cofounder and Academic Director, Tamás Vicsek, has made it to Nature Magazine again with an absolutely fascinating project: the creation of autonomous drones that flock like birds.

Tamás Vicsek

He coordinates the COLLMOT Robotic Research Project, a five-year program on the complex structure and dynamics of collective motion, funded by EU ERC.

Based on their findings on the collective behavior of birds such as pigeons, his team of Hungarian researchers created 10 self-organizing drones that follow rules of collective motion. "We came to the conclusion that one of the best ways to understand how animals move together is to build robots - flying robots", said Vicsek.

Equipped with GPS trackers and radios that allow them to navigate in formation, the quadcopters were tested in open-field environment for maximum authenticity. Instead of a central control, the drones use a flocking algorithm when their flying path becomes jammed, and wait for their turn while hovering in place.

Watch the video to see them in action:

FirmNet Online rebranded to OrgMapper

Our online organizational diagnostic tool, FirmNet Online, has undergone a rebranding, and will now officially become OrgMapper.

The new name focuses on the essence of the solution at hand, and crystallizes in a single word the underlying methodology our product offers.


Visit orgmapper.com to see the rebranding for yourself.

Primus Capital invests in the expansion of Maven7

Official press release on the recent happenings in our company's life:

Budapest, Hungary – Boston, MA
Primus Capital Fund Management Ltd. is investing more than 170 million forints (approx. 750,000 US dollars) acquiring a minority stake in Maven Seven Network Research Ltd. (Maven7), a provider of unique network research-based analyses and services. Through the capital investment, the 4-year-old company will further develop its online diagnostic tool, OrgMapper, and take it to Western European and overseas markets. It will also strengthen the sales activities of its US subsidiary and further develop its network analysis services for the media and pharmaceutical sectors.

Maven7 applies the latest results and innovations in network science to the business environment. Among its co-founders are such internationally acclaimed scientists of the discipline as Albert-László Barabási (Northeastern and Harvard Universities) and Tamás Vicsek (Hungarian Academy of Sciences, ELTE), who rightfully ensure the company's academic credibility.

Maven7 supports business decisions by transforming large amounts of hard-to-interpret data into actionable business intelligence.

The company's online Software as a Service (SaaS) platform, OrgMapper, allows its users, primarily in the business consulting sector, to conduct analyses in organizational development, the media, and the pharmaceutical industry, on the basis of which consultancies can provide M&A advisory, change management and other services to their customers.


Maven7 is the 10th investment of Primus Capital. "International competitiveness and execution built on the expertise of Central European physicists and engineers – this is the strategy of Maven7 and Primus Capital. We are proud to be working with such a fast-growing company and a team of extremely talented professionals in order to achieve international growth", added Zoltán Bruckner, investment director at Primus Capital.

Is football really a simple game?! The hidden networks behind Bayern's success!

The infographic was created by Avalanche. CLICK FOR FULL SIZE

With the power of network visualization, dynamics of football games can be understood better than ever. Maven7’s analyst team is a huge fan of sports (check out our last analysis about the chances of the Hungarian water-polo team at London Olympics), especially football. 

As everybody knows it, "football is a simple game; 22 men chase a ball for 90 minutes and at the end, the Germans always win". So then why do so many people admire this simple form of entertainment? Why do dozens of analysts try to predict who will win a certain game or championship? Why is betting a huge business? The answer is as simple as football, because this game is not simple at all! Behind every pass, attack and goal, human dynamics have a strong impact. Network Analysis can give a new approach to understanding team dynamics during football games. 

Our recent infographic shows the hidden networks of two finalists of Champions League’s 2013. Let’s face the big question; can network science provide the answer why Bayern won and not Dortmund? 

If you look at the pictures, similarities and differences are easily noticeable. Network structures and patterns resemble each other because of the same line-up structure. Two defenders (greens) had strong mutual pass connections at both teams, but Dortmund focused on the right and Bayern on the left back. Teams have preferred defensive midfielders - Schweinsteiger and Gündogan, they were the top choice to pass to in midfield. OK, so both teams are German and both have same line-ups, but what isthe difference then?

Why did Bayern win?

Dortmund’s midfielder, Reus was the preferred player to pass to from the attacking midfielders. The penalty that Dortmund received also came from a situation after a pass to Reus. 

At the attacking midfield, Bayern is more active on the wings, and their whole network is not that centralized as Dortmund’s. Bayern’s midfield played in a better cooperation; their network shows more mutual connections, and Ribery’s supportive role on the left wing makes the whole attacking part very successful. Unfortunately, Dortmund’s attacking midfield has no mutual connection, and the whole midfield has only one as well. In comparison; Bayern’s attacking midfield has mutual connection between Robben and Ribery, and the midfield also has 3 mutual connections (Schweinsteiger - Ribery, Müller – Robben, Ribery – Martinez), which may show stronger cohesion in the midfield. 

Also, the midfield players’ performance of the two teams indicates their teams’ performance. Schweinsteiger played and passed more actively and punctual (87 tries, 73 times successful – 84%) than Gündonan (56 tries, 31 times successful – 62%), and while Bayern had altogether 640 passes and their efficiency was 72%, Dortmund had only 448 passes with 60% efficiency. 

An interesting fact is, that those attacks, which started from the goalkeeper, are more likely happening by the players of Dortmund. In general, Dortmund’s defense played a more attacking role; while Dante passed mostly to the back, Boateng passed to the front. 

Maven7

The Harlem Shake Story - aka. Birth of a Meme

If you still have not heard of the Harlem Shake you must be living in a cave. Much has been written about the rapid and global spread of this catchy internet meme, yet little is understood about how it spread. A series of remixed videos along with a number of key communities around the world triggered a rapid escalation, giving the meme widespread global visibility. Who were the initial communities behind this mega-trend? SocialFlow took a look at 1.9 million tweets during a two-week period that included the words ’harlem shake’, or some versions of it.

The Harlem Shake itself is a dance style born in New York City more than 30 years ago. During halftime at street ball games held in Rucker Park, a skinny man known in the neighborhood as Al. B. would entertain the crowd with his own brand of moves, a dance that around Harlem became known as 'The Al. B. Though it started in 1981, the Harlem Shake became mainstream in 2001 when G. Dep featured the dance in his music video "Let's GetIt". While mining Twitter data, references to Harlem Shake (the original dance) were seen quite often prior to it becoming a popular meme. When someone tweets, "I just passed my final exams! *harlem shakes*," it's the equivalent of saying "I just passed my final exams! Look at me dancing!" While Bauuer's now infamous track was released on Diplo's Mad Decent label back in August 2012 (posted to YouTube on August 23 2012), it only accrued minor visibility for the first few months. Then February hit, and something changed.

The timeline below highlights the very first days as the meme was taking off. In blue, we see references to the 1980's dance *harlem shakes*, while the green curve represents Tweets that use the phrase 'The Harlem Shake', many of them linking to one of the first three versions of the meme on YouTube.

On February 2, The Sunny Coast Skate (TSCS) group establish the form of the meme in a YouTube video they upload. On the 5, PHL_On_NAN posts a remix (v2), gaining 300,000 views within 24 hours, and prompting further parodies shortly after. On Feb. 7, YouTuber hiimrawn uploaded a version titled "Harlem Shake v3 (office edition)" featuring the staff of online video production company Maker Studios. The video becomes is a hit, amassing more than 7.4 million views over the following week, and inspiring a number of contributions from well-known Internet companies, including BuzzFeed, CollegeHumor, Vimeo and Facebook.

Social Flow looked at the social connections amongst users who were posting to the meme. This gave them the ability to identify the underlying communities engaging with the meme at a very early stage. In the graph above each node represents a user that was actively posting and referencing the Harlem Shake meme on Feb 7 or 8 to Twitter. Connections between users reflect follow/friendship relationships. The graph is organized using a force directed algorithm, and colored based on modularity, highlighting dominant clusters - regions in the graph which are much more interconnected. These clusters represent groups of users who tend to have some attribute in common. The purple region in the graph (left side) represents African American Twitter users who are referencing Harlem Shake in its original context. There's very little density there as it is not really a tight-knit community, but rather a segment of users who are culturally aligned, and are clearly much more interconnected amongst themselves than with other groups.

After a similar analysis on the following two days (Feb 9 and 10) different communities can be seen emerging, resulting in a much more tightly knit graph structure. While the same dense cluster of musicians and DJs (in turquoise) still exists, there are substantially more self-identified YouTubers both across the US and the UK. At the same time there's a significant gamer / machinima cluster that's also participating, as well as a growing Jamaican contingent, and quite a few dutch profiles (purple -- left). Additionally, we see various celebrity and media accounts who caught on to the meme -- @jimmyfallon, @mashable and @huffingtonpost. By capturing the two snapshots, we can also make sense of the evolution of the meme as it becomes more and more visible. At first, loosely connected communities separately humored by the videos. Within days, we see major media outlets jump on board, and a much more intertwined landscape. We see different regions in the world light up, and identify communities of important YouTube enthusiasts who effectively get this content to spread.

Memes have become a sort of distributed mass spectacle, a mechanism that both capture people's attention, and define what is "cool" or "trendy." We see more and more companies and brands try to associate themselves with certain memes, as a way to maintain a connection with their audience, gain the cool factor. Pepsi did this with the Harlem Shake and saw an incredibly positive response. 

As we get better at identifying these trends and trend-setting communities early on, the pressure to participate will rise. As social networks become globally-intertwined, we're witnessing a growing number of memes conquer the world at large. These moments are critical points in time, where there are significant levels of attention given towards a specific entity - be it a joke, funny video or a political topic. Piecing together data from social networks can help us identify critical points in time, as well as the underlying communities and trendsetters for the humor-based memes, or the agenda setters for politically-slanted ones. The only question is: what will be the next one, cashing in on it 15 minutes?

Hungry for more? Read the full article on HuffPost.