LATI: A better way to measure influence on Twitter?

I’ve never been comfortable with attributing digital influence to the number of followers someone has on Twitter.

To me, it’s more a measure of your longevity on the platform. The longer you have been on Twitter, the more followers you will have collected over the years.

Sure, the quality of your tweets and other variables will have an effect, but simply comparing the raw number of followers among tweeps is not really comparing apples with apples.

I was ruminating over this when it dawned on me: why not divide the number of followers by the number of years the person has been on the platform? That will remove the variance due to longevity from the equation.

For example, I currently have 831 followers and my Twitter age is 2.1 years, so my Longevity Adjusted Twitter Influence (LATI) is:

831 / 2.1 = 396

According to convention wisdom, someone who has 1500 followers is much more influential than I am. In absolute terms that may be true, but if their Twitter age is 4 years, their LATI is 375 – which suggests I am relatively more influential than they are. That means I’m on track to becoming more influential overall.

Compare that to someone who joins Twitter and attracts 200 followers in 3 months. That’s a LATI of 800 which blows both of us out of the water.

In the short term I imagine a typical person’s LATI would follow an s‑curve, whereby they take a while to attract followers in the beginning, then they ramp up as word spreads, then they plateau out again as their target demographic is exhausted. Over time, their LATI will decline as the years rack up without significantly more followers.

In contrast, truly influential people will continue to attract followers into infinity, so their LATI will remain high.

Now I’m no mathematician, so my logic may be all screwed up. But to me it’s more meaningful because it levels out the playing field.

Of course, the metric doesn’t recognise who is following you. Someone with 10,000 followers won’t be very influential if those people have neither the means nor the inclination to act upon their pearls of wisdom.

Conversely, someone with only 3 followers will be incredibly influential if those people happen to be the President of the United States, Rupert Murdoch and the Head of the European Central Bank.

So notwithstanding complicated and opaque measures like Klout, LATI provides an open and convenient snapshot of digital influence. At the very least it’s fun to toy around with.

The A to Z of learning

It all started with a tweet by Anne Bartlett-Bragg (@AnneBB) observing an instance of the term s-learning representing social learning.

Amused by our industry’s obsession with single letter prefixes, I replied facetiously that I preferred the term slearning – simply because it sounds so awful.

Then Anne suggested we play an alphabet learning game, and she proposed the first neologism: a-learning is awful learning? action learning? adaptive learning?

Well that was a red rag to this nerdy bull, so I replied with b-learning is book learning. In the blink of an eye we roped in Penny Wheeler (@pennyjw) and Claire Brooks (@clairebrooks) as we embarked on a
26-letter journey of frivolity.

All fun aside though, assigning 26 letters to learning is a lot harder than you might think.

Sure, you can make up anything (eg zebra learning), but if you adhere to the spirit of the game and confine your answers to terms that are pedagogically meaningful, the level of difficulty rises.

More than just a game, the exercise prompted me to critically reflect on the broad range of instructional approaches that are adopted in the digital age.

So what did we come up with?

• a-learning is awful learning, action learning, adaptive learning
• b-learning is book learning
• c-learning is Confucian learning
• d-learning is distributed learning
• e-learning is enhanced learning
• f-learning is free learning
• g-learning is great learning, generative learning, granular learning
• h-learning is hidden learning, holistic learning
• i-learning is incidental learning, integrative learning
• j-learning is just-in-time learning
• k-learning is kinaesthetic learning
• l-learning is learning to learn
• m-learning is meta learning
• n-learning is new learning
• o-learning is objective learning, organisational learning
• p-learning is learning from other people
• q-learning is quantum learning, quick learning, quality learning
• r-learning is research oriented learning
• s-learning is social learning, socially networked learning
• t-learning is transformative learning
• u-learning is universal learning
• v-learning is video game learning, voracious learning
• w-learning is we learning
• x-learning is xenogamous learning
• y-learning is Gen Y targeted learning
• z-learning is Zen learning

No doubt you noticed that we tended to avoid the obvious (eg electronic learning, mobile learning).

In fact, I think we ended up with quite a thought-provoking list.

Wanna play?

Anyone can play the A to Z Learning Game.

Simply follow the #azlearninggame trend on Twitter and chip in the next answer.

Just remember to use the hashtag, and try to pick something unique.

If it’s abstract or obscure, justify it within the 140 character limit.

Go on, have a go!