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24 hours of global tweets about Sir Alex Ferguson retirement, from the rumour to the announcement to the aftermath through the lens of two visualisation approaches: the streamgraph and the rose.

Streamgraph > Tue 07 May – 10 pm / Wed 08 May 10 pm


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Nightingale Rose or Coxcomb Diagram > Tue 07 May – 10 pm / Wed 08 May 10 pm

 

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Data based on 100% of public tweets collected, analysed and visualised with Pulsar TRAC 

Anatomy of Two Memes

As you might have heard, we’ve just launched a new social media intelligence tool Pulsar TRAC, and along with it, we’re releasing a new series of data studies called How Stuff Spreads in collaboration with our social data partners Datasift.

How Stuff Spreads will look at how digital content (videos, articles, websites, and images) travels the social web. This, the first instalment, looks at how two memes spread on Twitter: Gangnam Style vs Harlem Shake.

Screen Shot 2013-05-08 at 18.12.24

Gangnam Style and Harlem Shake were viral phenomena, generating thousands of spin-off versions and billions of views. By using Pulsar TRAC’s Content Tracking technology, we are able to track any social media conversation containing a specific URL and analyse who is talking about it, gateways and hubs, topics of discussion, geography of the discussion and key channels.

Me (@abc3d) and Jess Owens (@hautepop) wanted to understand how Gangnam and Harlem became global memes. So we set out to compare how the top 5 versions of each video were shared on Twitter, looking at 8 dimensions of each meme:

Shape: Number of shares per video, over lifetime of the meme

Lifespan: Number of consecutive days where people shared the meme 500+ times

Popularity: Number of unique users sharing the meme over its lifetime

Shareability: Total Twitter shares per each million of YouTube views

Globality: How international was the meme?

Amplification: How influential were the people who shared the meme

Variation: How much did attention to the meme vary day-by-day?

DiffusionNetwork: Hubs and nationalities who drove the spread of the meme

Here’s what we found out.

1) Memes have different shapes. Gangnam Style showed a top down or ‘vertical’ pattern, with the original video generating 10x as many YouTube views and shares as any of its variations. Conversely Harlem Shake was more bottom up or ‘horizontal’ in its dynamic, with the original seed sparking thousands of variations, some of which did better than the original in terms of views and shares.

Bubble size comparison of Harlem Shake and Gagnam Style

2) The shape of a meme affects its lifetime. We defined a meme as ‘live’ (popular and actively shared) as the time when it was getting at least 500+ URL shares on Twitter per day. Whereas Gangnam Style lived for 172 consecutive days, Harlem Shake only survived for 29.

Why did Gangnam, the “top down” meme, live over 5x longer than the “bottom up” Harlem Shake? A possible clue may come from the three-part-process of social movement formation which Charles Duhigg describes in his book “The Power of Habits”:

“A movement starts because of the social habits of friendship and the strong ties between close acquaintances.

It grows because of the habits of a community, and the weak ties that hold neighborhoods and clans together.

And it endures because a movement’s leader gives participants new habits that create a fresh sense of identity and a feeling of ownership”

Whereas Gangnam Style offered a strong top-down narrative with an easily identifiable leader in Psy, Harlem Shake had a more distributed narrative with no real leadership and guidance outside of the format. Consequently it didn’t succeed in creating a ‘habit’ that would outlive the interest from the local and community networks who where the real engine behind this meme.

3) Regardless of their shape, memes spread in waves. Both memes showed a very spikey distribution, with attention to the video fluctuating dramatically day-by-day. We quantified this variation by first calculating the standard deviation of the daily sharing rate (i.e. how much sharing levels varied day by day), then dividing by the mean to give us the coefficient of variation.

Typically all the videos saw a lot of variation in the rate they were shared, with Gangnam Style being more consistent (196% variation) then Harlem Shake (338% variation). But three videos stood out for showing much more variability: YouTube Gangnam Rewind (807%), Britney Spears learning Gangnam on the Ellen Show (574%) and basketball team Miami Heat’s Harlem Shake (517%). These videos each saw a massive launch spike – e.g. Britney with 15,792 tweets carrying the link on September 11 2012, and Miami Heat’s Harlem Shake with 63,927 on March 02 2013.

How did they achieve this? Each video was led by an individual or organization with massive reach – YouTube and Britney Spears both have 26m Twitter followers, and Miami Heat has a strong community of 1.2 million. This means they were able to activate a big existing audience to get the video out very quickly on Day 1 – hence the big spike in sharing. But within a couple of days, that audience was saturated – everyone who’d be interested had already seen the video. The Britney Spears variation of Gangnam Style, linked to The Ellen Show, was only newsworthy within a brief timeframe. Miami Heat’s take on the Harlem shake was particularly relevant to the basketball community and expired once the “local” reach was somewhat exhausted. So sharing dropped off precipitously – hence the big variation score.

It’s almost a risk to be a social media influencer – you can activate a large audience very quickly, but that attention can be burnt through equally fast. By comparison, the Gangnam Original video had one of the lowest variation scores (114%). Psy was new to Western and Latin American audiences, so the video travelled more slowly through social networks – but this helped attention sustain for fully six months.

Harlem Shake network compared to that of Gagnam Style

4) Small communities drive virality. The relationship between communities and viral spread is reinforced by the fairly high density and modularity of both the Gangnam Stye and Harlem Shakes networks. This highlights the key role of small communities in spreading the meme. Within the Gangnam Style network, 14% of the people sharing the link passed it on or grabbed it from someone, while within the Harlem Shake network the connected sharers increase to 17% of the overall pool of users. These figures are remarkable considering the globally dispersed diffusion of the memes.

By contrast, influencers only accounted for a small percentage of the total buzz. Out of 767,000 unique mentioners of the Gangnam Style videos only 64 generated more than 100 retweets and only 8 more than 1000. Out of 173,000 unique mentioners of the Harlem Shake videos, only 9 generated more than 100 retweets. That means that for Gangnam Style less than 5% of the total shares were directly connected to the influencers, and for Harlem Shake only 1%.

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5) Both memes transcended physical geography, even though both were born out of specific geographic areas and subcultures.

We measured the memes’ Globality (% of shares coming from countries other than the top one, usually the USA). Both memes were very international, but Gangnam Style turned out to be more global then Harlem Shake (78% vs. 63%) This makes intuitive sense – Gangnam Style started in Korea and spread to win massive popularity across North America, Latin America and Europe. Most viewers didn’t understand the lyrics, but the strong visual character meant this didn’t matter. By contrast, some of the Harlem Shake videos were much more geographically and culturally specific – particularly the Miami Heat basketball Harlem Shake, which got fully half (49%) of its sharing from within the United States.

This is also clearly shown in the network analysis, where the number of retweets spanning from the central nodes of the Harlem Shake meme network confirms this US-centric pattern of engagement. Conversely the central nodes in the Gangnam Style meme network are connected to a very diverse range of countries.

6) Popularity doesn’t mean Shareability, and Shareability doesn’t imply Popularity. While Harlem Shake turned out to be 3x more shareable then Gangnam Style, it still ended up being 4.5x less popular in terms of the number of unique users sharing it.

How did this happen? This is certainly connected to the higher mainstream coverage of Gangnam Style which lowered its currency in social media – there’s little value in sharing something people are seeing all over the TV. It’s also connected to the greater iteration and ‘localization’ of the Harlem Shake meme. This made its videos more relevant to hundreds of small local communities across the globe – so the Norwegian Army video was heavily shared in Norway, the Miami Heat video in the United States and so on. Essentially Harlem Shake had currency but didn’t have scale. Gangnam Style had less currency but had massive scale.

It’s a difficult balance for a meme to strike. Community drives Shareability but doesn’t give you Scale (Popularity). Top-down influence drives Scale (Popularity) but kills Shareability. While Shareability is a key requisite of virality, scale is what enables and sustains exponential growth.

7) Memes are like currencies: you need to balance accessibility (or ‘money supply’) and inflation. Gangnam Style became globally accessible through top-down mainstream sources (High Popularity), but this gave it high social inflation so it wasn’t valuable to share (Low Shareability). However, scale sustained its long term growth. Harlem Shake was not as easily accessible because it was driven more by small communities (Low Popularity), but for the same reason, being less easily accessible, it remained highly valuable (High Shareability). Lack of scale was what made Harlem Shake growth short-term and eventually killed it prematurely.

graphs for Lifetime, globality, popularity, amplification, variation, and shareablility

Conclusions: 8 things we learnt about how stuff spreads in social media

Based on what we’ve seen from studying the spread of the Gangnam Style and Harlem Shakes memes on Twitter, we see 8 common things to watch out to make things go viral:

  • Bursts and Rises: 2 models of virality. The Burst model is bottom-up: the variations are more powerful then the original seed and there’s no clear leadership or narrative. The meme relies on community relevance to spread. The Rise model is top-down: the original seed is always stronger than its variations and has a clear leader dictating the narrative. Bursts spread widely more quickly but don’t endure. Rises spread more slowly and less widely but they tend to endure because the meme has a focal point. Chose your model of virality and plan accordingly.
  • Triggers. Whatever the model, virality is triggered by surprise, cultural relevance to a community, and endorsement by a leader or the media.
  • Waves. Whatever the trigger, virality is not a steady affair; it spreads in waves and spikes.
  • Communities drive viral spread way more than influencers.
  • Glocality. Memes transcend geography but a successful meme needs a balance of both local relevance and global appeal.
  • Leadership. A meme needs a focal point to live longer. Virality is only sustained through a strong narrative and leadership.
  • Slow and spikey wins the race. Weak ties and communities sustain for weeks but they don’t give you scale in the short term. Top-down media and celebrity endorsement gives you instant scale but burns out within a couple of days by decreasing the shareability of the meme.
  • Memes are like currency: you need to balance supply (or accessibility) and inflation. In order to achieve high shareability and high popularity the meme supply has to be expansionary but strategically controlled so that it doesn’t negatively affect its shareability. This at the same time gives the meme the scale that can trigger and sustain exponential growth.

Dive into the Gangnam Style diffusion network

Dive into the Harlem Shake diffusion network

* For more information contact the authors at Francesco [at] facegroup.com and Jessica [at] facegroup.com or visit www.pulsarplatform.com

 

Our intrepid Chief Innovation Officer, Francesco D’Orazio, is off to Budapest next week to be a keynote speaker at ESOMAR’s Day of Market Research event. The event is all about how to understand big data, which is perfect for Francesco who is the chief technologist behind the recently launched Pulsar TRAC, our advanced social intelligence platform that pushes social media research beyond keyword tracking.

ESOMAR logo

Francesco will be talking about 7 practical approaches to understanding big data. He will be speaking about how to gain insights and value from the social web by introducing a methodological framework for big data and social media research. Before jumping into the 7 practical research approaches and techniques, he will be doing an overview of the key tools and the different types of data that are available, as well as how to gain access to them.

If you can’t make it to Budapest to see Francesco’s presentation, you can still join our similar webinar “5 Things to Do with Social Data That Aren’t Keyword Tracking.” Francesco is presenting this webinar on May 8th at 11am EST.

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Francesco D’Orazio is the Chief Innovation Officer at Face. Connect with him on LinkedIn here, or share your thoughts about Big Data with us at @FaceResearch.

With all the talk about online influencers over the past few years, you’d think they were the holy grail of online marketing. Klout has made a business of it and many bloggers use sponsored posts to help pay the bills. But, the funny thing is, if you want to get the word out about your brand, product, or cause, influencers aren’t actually where you should be focusing your efforts. Let me explain.

Yes, influencers do help – I’m not going to deny that. Get Lady Gaga to tweet about your charity or fashion statement, and tons of fans will go out to investigate it. Want mothers to start using your diapers? Yes, try to get the mommy bloggers to write something up about them. But that tactic will only do so much. It leads to a spike in sales, but not a long-term trend. As a word-of-mouth marketing strategy, it’s limited.

Oprah Winfrey

This has been known in the publishing industry for quite some time as an effect of book clubs. An initial spike is launched by one large book club, like Oprah’s book club (she’d be your influencer), but the long-term trend continues as smaller book clubs pick up the torch and then those readers pass on the good book to their friends in turn.

This phenomenon becomes traceable as a long tail. It’s not just about the niche topic, it’s about the niche communities, of which there may be several for each topic.

We did a joint study with our sister agency Blonde not too long ago that illustrates this nicely. This study was actually where we developed the concept for the content tracking feature of Pulsar TRAC, our recently launched advanced social intelligence platform that pushes social media research beyond keyword tracking.

Meet Irn-Bru

Irn Bru

Irn-Bru is a soft drink that’s spectacularly popular in Scotland. So much so you wouldn’t be far off calling it the national Scottish drink. In fact it is one of the rare carbonated beverages to outsell Coca-Cola in any market.

Coming from such a position of strength in its main market, the marketers at Blonde decided to do something a little different when launching a recent commercial. This allowed us to demonstrate the power of small groups in spreading something – and even compare this with the power of influencers.

Releasing a Commercial

Blonde released this commercial by giving it to just one person: a regular young woman on Twitter who had won a competition. Rachel Orr (@larachie on Twitter) started out with just 153 Twitter followers – bang on average. Irn-Bru promoted her account and managed to increase her follower count to 329 – still not exactly Lady Gaga levels – before they gave her the link to the YouTube commercial.

But a few of those followers were “influencers”. Blonde encouraged some of Scottland’s top tweeters to follow @larachie with the incentive that they’d use this as a way to measure their influence. Some of these people included @AndrewBurnett, Head of Social at Yard Digital, and the band Bleed from Within (@bleedfromwithin).

After @larachie tweeted the initial YouTube link, the video reached 100,000 views in one day, led by her but amplified by these influencers.

Small groups trump influencers (at sustaining growth)

So, we have learned that influencers are really awesome at jump-starting an ad campaign. Likewise looking back to my book club example, influencers jumpstart sales. (Thank you, Oprah!)

But how do you keep those sales growing? This is where small groups trump influencers. Small groups, not big influencers, are the Holy Grail of word-of-mouth marketing. Sticking with our book club example, these key groups are the smaller book clubs, the ones that hear about a book from the big influencers and then bring it to people in their community, who then carry the book to another gathering or tell a friend who is part of another book circle, and so on. This is how something goes from an initial spike to a burgeoning trend.

We can see this play out online. In the microcosm that is Twitter, that Irn-Bru commercial continued to grow even after the influencers had played their initial role. Over the next 21 days, the commercial’s YouTube stats increased from 100,000 to 650,000 views. That’s about 26,000 people per day. This coincided with the commercial being passed around smaller, interconnected groups.

The visualization above  depicts not the number of shares or mentions, but the number of connections each account has with other accounts that have also mentioned the YouTube video. As you can see, quite a few are really small – those would be the small groups. Those are the ones that are apparently behind the growth in views for the next three weeks after @larachie launched the commercial.

Yes, the influencers were really helpful. Yes, they probably jump-started the whole thing. But the ones who kept it going, who probably got the video mentioned on the Poke’s Viral of the Day three days after the launch, were the small groups.

Here’s the difference:

  • Influencers: Contribute a big spike, good for a jump start and initial push
  • Small Groups: Contribute more sustained engagement and spread, good for the long term

Find content small groups can get behind

This commercial managed to appeal to many small groups because it was funny, original, and took creative risks. And, of course, because it was Irn-Bru and in Scotland.

This won’t always be the winning content recipe (especially if you’re not Irn-Bru and in Scotland). You need to find content that appeals not just to your audience, but which appeals to specific niches and communities within your audience – the more the better.

Once you do that, your content has a higher chance of spreading naturally – virally. You may still want to include some influencers in your release strategy, of course – It’s not an either/or situation. But if your content isn’t something small groups can get behind, it won’t travel.

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In May we’re releasing a substantial new study into the dynamics of viral video. Sign up for our mailing list here to be one of the first to know.

This Thursday, our Chief Innovation Officer, Francesco D’Orazio, will be presenting the first installment of the “How Stuff Spreads,” at this year’s Big Data Week in London. This study dissects and compares two of the biggest Internet memes by analysing when, where, how and why millions of Twitter users shared the top five videos for each meme over the past 12 months.

Big Data  Week London

The “How Stuff Spreads” study used the diffusion mapping tools on Pulsar TRAC in order to look at how a series of viral videos spread on social media. We wanted to answer how they grew from zero to millions of views. By understanding who, when and where the videos were shared and what they have in common we could identify insights around how these videos spread.

Francesco will be presenting the study  Thursday, April 25th, as part of the Putting Data to Work event hosted by Edd Dumbill, the program chair for the O’Reilly Strata Conference and the O’Reilly Open Source Convention. The event will be held at the Imperial College, London from 9:30am until 6pm.

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Want to learn more about how to get behavioral and contextual insights from social media data? Join us for “5 Things To Do With Social Data That Aren’t Keyword Tracking” on May 8th. Registration is open.