OCUK, if you could monitor the world's mood on ANY topic, what would you look at and why?

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Let's say hypothetically you could monitor the world's mood on any topic. E.g.,"cheese". So as a function of time, you'd know how popular cheese is, and whether people feel good about cheese or not.

What would you monitor? And why?

Now let's change the question, say you wanted to somehow add value, i.e. make cash from this. How would this information be of use in this situation?

I've been thinking about this topic a lot lately, and I can't answer it properly. Thought I'd ask you!

Caveat: you can never know the feelings of an individual person. Just as an aggregate, e.g. say by country or city or region. Something like that.
 
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But let's say it's in real time. Market research is delayed and not quite as refined. Let's say we can plug into every person's brain and say, if you're thinking about "cheese", how do you feel about it, say on a scale of 1-10.
 
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Market research into stock values, for buying and selling stock?

I'd like to know the world's mood on things like doomsday, and countries, and religion. I'd love to know the mood on Islam, and I'd love to know what those from Islamic countries think instead of stereotyped Westerners. Like do people from Saudi Arabia find it as disgusting as we do or do they support their religion as strongly now as they did 20 years ago after all the things that have been done in it's name.

That isn't me trying to provoke a response, just curiosity.
 
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If I could 'plug' into everyone's consciousness like that, the last thing I would care about was whether the world liked cheese.......
 
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You can already monitor the 'worlds mood in real-time', it's called sentiment analysis (and almost all big brands have monitors already set up). Any social monitoring tool will be able to search and find all references (facebook, twitter, blogs, news etc) related to a keyword that you provide it with and allow you to view the sentiment shifting from the positive to the negative etc. A while back a company was claiming on using this to deal in shares. The problem with it is that it's never going to really work very well - for example if I say that "the customer service at Apple is UNREAL" do I mean it's really bad or good? It turns out a high percentage of human interaction is unclear like this unless you have a LOT of context.
 
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Scottish Independence. Show that waste of space we call first minister just how out of touch with his country he is!

/Salsa
 
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You can already monitor the 'worlds mood in real-time', it's called sentiment analysis (and almost all big brands have monitors already set up). Any social monitoring tool will be able to search and find all references (facebook, twitter, blogs, news etc) related to a keyword that you provide it with and allow you to view the sentiment shifting from the positive to the negative etc. A while back a company was claiming on using this to deal in shares. The problem with it is that it's never going to really work very well - for example if I say that "the customer service at Apple is UNREAL" do I mean it's really bad or good? It turns out a high percentage of human interaction is unclear like this unless you have a LOT of context.

Yep - I'm aware of this. It was called Derwent Capital Markets.

But I'm thinking of something beyond simply stock prices. Haven't you ever thought about what it would be like to read the minds of others? This is the same, but on an aggregate level. Surely the process of aggregation does not diminish the appeal of the information?
 
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Yep - I'm aware of this. It was called Derwent Capital Markets.

But I'm thinking of something beyond simply stock prices.

No, sorry for the confusion - the stock market use was just an example. You can do this for any word or phrase already. It's built in to almost every social media monitoring tool. Raven Tools, for example, has one built in. I've used it a bunch of times to report on brand mentions in crisis management situations, but you could use it for anything. The problem, as I mentioned before, is the issue of clarity over whether a statement really is negative or positive. I've seen enough audiences that can't decide whether a tweet was meant positively or not - let alone an algorithm. As a rough estimate of mood though sentiment analysis works well enough.
 
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