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.

Connecting the Community

We all live in multiple on-line communities, but what do these communities look like? Where are we located in each of our communities, and what role do we play?

The diagram below shows an actual on-line community [OLC]. Every node in the network represents a person. A link between two nodes reveals a relationship or connection between two people in the community -- the social network. Most on-line communities consist of three social rings -- a densely connected core in the center, loosely connected fragments in the second ring, and an outer ring of disconnected nodes, commonly known as lurkers. Communities have various levels of belonging -- each represented by one of these rings. You may belong in the core of one community, while being a peripheral lurker in another.

In the above diagram, we see three distinct types of membership in our community -- designated by blue, green and red nodes. The proportion of nodes in each ring in this population is fairly typical of most on-line communities -- the isolates [lurkers] outnumber the highly-connected by a large ratio. The outer orbit in the network above contains the blue nodes. They have been attracted to the OLC, but have not connected yet. The blue nodes contain both brand new members, who have not connected yet, and passive members who have seen no reason to connect. The passive group is the most likely to leave the OLC, or remain as absorbers-only of the content in the community.

The green nodes have a few connections -- usually with prior acquaintances. They are not connected to the larger community -- only to a small, local group. They do not feel a sense of true membership in the larger whole, though they may identify with it. The small clusters of friendships amongst the greens can be maintained by other media and do not need this particular OLC to survive. They are also likely to leave or become passive and will likely do so in unison with the rest of their small circle of friends.

The inner core of the community is composed of red nodes [zoomed-in view below]. They are very involved in the community, and have formed a connected cluster of multiple overlapping ego networks. The leaders of the OLC are embedded in this core cluster. The core members will stay and build the community. Unfortunately they are in the minority. The core node consists of usually less than 10% of most on-line groups -- sometimes they are as few as 1% of the total OLC. Although small, they are a powerful force of attraction. It is the core that is committed and loyal to the OLC and will work on making it a success.

Online communities and social networks are often conceived and developed by businesses and organizations that focus on: "How can we use the online community to benefit us?" Focusing only on how to utilize the community, leads many organization to failure in building these communities! They fail at community development by not creating a strategy that makes sure their target audience is gaining a positive experience and practical benefits from participating in the community. It is amazing how many organizations try to build on-line social networks while ignoring the needs of the very people they are trying to attract and influence! It is then no surprise when large chunks of their target group leave when the "next big thing" comes around: SixDegrees-->Friendster-->Orkut-->MySpace-->Facebook-->Next? To build a vibrant and growing OLC, you need to support natural human behavior, not work against it. You need to think sociology, not just technology.

The field of social network analysis [SNA] gives us tools to both know the net and knit the net. SNA maps and measures the paths of information, ideas and influence in the community. SNA reveals the emergent patterns of interaction in organizations and communities and allows us to track their changes over time.Growing a community is not just adding new members. It requires adding both people and relationships -- nodes and links. Node counts are important in social networks, but it's the relationships -- and the patterns they create -- that are key! A community thrives by its connections, not by its collections! It's the relationships, and the prospect of future relationships, that keep members active and excited.

Source: http://orgnet.com/community.html

Mapping the web

A Russian coder by the name Ruslan Enikeev has created something extraordinary: The Map of the Internet. The map depicts a network based on traffic, with each dot representing a website, and each switch a link. The stronger the link (the more often people went from one site to the other) the closer they become on the map. The bi-dimensional scheme gathers information from over 350 million sites from 196 countries, and also works with a color scheme: sites relative to a country are painted the same, Russia is red, China is yellow, Japan is purple, and North-America is light blue. For the curious geeks physical and quantum-physical examples are drawn, and a mathematical analogy is also accessible to help with understanding the method. Different clusters are arranged according to their content. The network is based on data until the end of 2011. The purpose of the project was „an attempt to look into the hidden structure of the network, fathom its colossal scale, and examine that which is impossible to understand from the bare figures of statistics.”

The Hungarian segment shows that the most visited site up until 2011 included Google, the news portal Index, the blogging site blog.hu, origo, and Iwiw, the social networking engine that ruled the market before Facebook became popular. Other circles indicate frequent switches between university sites and funny blogs like sg or demotiváló, Imdb is the biggest foreign blog, Hungarians visited last year.

The project came to life with the help of Google Maps API and russian creative agency Positive Communications and claims to have no financial purpose but entertainment.            
The application operates under the following address.