What happens on #Twitter when someone like #Mandela dies

I was going to title this post – ‘What billions of silent voices screaming at the same time look like’ – but it seemed too dramatic.

As I was about to release the pre-beta of my new app Hashies, the news came on the wire that Nelson Mandela had died. I wasn’t particularly shocked – more relieved actually. I do feel like I have lost a beloved grandfather – I think most of the world feels the same. But in the last few months, the situation around him and the media frenzy was grotesque to say the least. I wished nothing more than a peaceful passing on for Mr Mandela and when it came I felt only relief and gratitude for a beautiful brave life.

Hashies tracks what people are saying on a hashtag in near real time. Given the news, ‘#Mandela’ seemed the way to go. Before I heard the news – it was going to be ‘#JustinBeiber’ – glad it wasn’t!

Enough said, here is what it looked like.

And just to be sure – there is no one quite like Mr Mandela. And there is unlikely to ever be. RIP Madiba.

Why Sentiment Analysis is Promising But Currently A Waste of Time.

I love you even though you beat me.

Even though you don’t love me.

Even though you shout at and deride my efforts.

Even when you disagree with my existence.

Even when you vilify me for the air that I breathe.

I cherish you despite the cruel words with which you punish me.

You cherish my destruction even when I detest that smallest of inconveniences to you.

Even when the only thing that would satisfy you would be my death.

My cruel killing at the hands of the most vicious destroyer.


What do you think the above is about. Is it overwhelmingly negative or inherently positive?  What is its sentiment?

Here is what one of the ‘leading sentiment analysis’ tools determined it was about:

Screenshot 07:03:2013 11:41-4


I had need to explore where Sentiment Analysis is today because I might have a future need to harness its ‘power’.  Well I was fairly disappointed.

Scientists (in this case computer ones) will have you believe that sentiment analysis is so advanced and mature as to be reliable. Bullshit.

They call it ‘Sentiment Analysis’ and this projects an illusion of precision, reliability and worse still they sell it as something you should base decisions on.

It is no more than word counting and weighting.
Fortunately it is simply a case of mislabelling. This is not ‘Sentiment Analysis’ it is Content Analysis. No more than looking in a basket of citrus fruits and counting lemons vs oranges vs limes. The trouble is when they sell it as a indication that the farmer has kidney stones!

Sentiments deal with the emotional message the content is trying to communicate. Businesses deal with the emotive state of their customers and any indication of how a customer feels might provide competitve advantage and an opportunity to profit (in goodwill or stone cold cash).

I say that Sentiment Analysis is promising because I believe that machines can learn to determine the emotional meaning of any content, but if this is the current approach then I fear that we are a long ways off.

Currently the best way I know to understand sentiment is to have a conversation, to listen and be reasonably educated enough to understand what your co-communicators’ needs are. To look beyond the words used (they may be the wrong ones).  I wish that more businesses recognised this and invested accordingly instead of wasting time, energy and money on something that promises so much and delivers so little.

BTW – using the same engine, this article scored -.107 and could be about renewable energy, hardware, technology or investing. Ouch!

Screenshot 07:03:2013 12:40