in 2011, sentiment analysis for Twitter was just beginning to phase into mainstream business conciousness.

So, when London-based DCM Capital announced a hedge fund based on Twitter sentiment it was a bold move that ultimately didn’t gain the exposure the company were looking for, and the project closed after a few short months.

The company has continued to refine its algorithms however, and recently spoke to Bloomberg about their latest project: A spread-betting platform based entirely on social media sentiment…

There’s a huge range of tools out there that claim to be able to tell you if you’re hot or not with tweeters of course, from free tools like Klout and Kred, up to large paid-for systems designed for enterprise usage, but so far I’ve yet to see a single one that can accurately track human emotions, let alone in real time.

Generally speaking, human interactions are just too complicated, and machines will always struggle to track variables like sarcasm (and we’re talking about the internet here, so snark is par for the course).

Despite these problems, accurate analysis, especially tied to provable financial ROI, is the holy grail for many marketers. More and more we’re hearing that businesses want to use social to directly affect the bottom line (We do as well, we are a business after all). 

In the world of finance analysis moves at incredible speed, often faster than human minds can deal with. Trades are made based on miniscule changes mapped automatically, with automated bidding making split-second decisions alongside human operators.

One of the clear attractions of social media to the financial world is its immidiacy. We’re constantly told that social is real-time. Twitter is a live data stream, which makes it perfect for customer response. Get your customer satisfaction levels up and you’re stock will rise. At least, that’s the theory.

Unfortunately when it comes to extracting truly valuable insight, the real power lies with those who have the time and inclination to look at social as a data store as well.

Sentiment often isn’t a key indicator in financial performance if viewed in real-time.

Customers often blow up on Twitter over small transgressions. Once the problem is solved, then very few of those complaining would ever take the time to thank the community manager who helped them out.

If we have a problem we tend to make it public, so people will often say “Hey @CompanyX, the product I ordered hasn’t shown up!”. Nice and visible. Once @CompanyX fixes this though, if customers bother to reply then it will likely be “@CompanyX thanks, that’s great” Rather than “Hey everyone, CompanyX do a great job”. This is par for the course, getting genuine evanglism is a lot harder than getting a positive response

Likewise, social sentiment isn’t the be-all and end-all here.

Social responses only cover a small preportion of customers with the inclination to get in touch or voice their displeasure on social platforms. Many of us simply don’t take the time to hunt out a Facebook page to really complain.

I only tend to turn to Twitter when I get fed up with being stuck in the call line (and usually I get an almost immidiate response. Twitter is the que-jumpers medium of choice). This means that by the time a complaint actually hits Twitter, I’m getting pretty exhausted with the regular channels, so I’m already riled up and ready to rumble.

If I moan about you on Twitter, you can be pretty sure I’ve already tried to moan somewhere else, so social complaint levels are often inherently skewed. 

The key for businesses on Twitter is not to rely on “Positive/negative/indifferent” as an indicator, but rather to use a variety of tools across different channels to judge sentiment over time. Likewise don’t just wait for customers to tell you; go out and ask them. And always question your data and consider underlying bias carefully. 

IF DCM can really accurately map stock prices through social they’ll have something very special indeed on their hands, and it will be interesting to see how this plays out in the coming months, but untilthen it’ll be a brave investor indeed who puts their money where their Retweets are. 

Do you think sentiment analysis is accurate enough to base real transactions on? I’d be fascinated to hear from any of you who use sentiment systems in the comments.