Thomson Reuters Taps Into Twitter For Big Data Sentiment Analysis

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Twitter bases the majority of its revenue on advertising in and around its main content river, but a new service from Thomson Reuters points to how it also continues to build up its position as a big-data provider to different vertical sectors. Thomson Reuters is now incorporating sentiment analysis gained from Twitter for its Eikon market analysis and trading platform. The commercial terms of the deal are not being disclosed but to be clear it is not a deal directly with Twitter: a spokesperson confirms that it will be “combining a number of third-party and proprietary Twitter feeds for this service.”

You can think of this as an expansion of the kind of Twitter mining first tried out by Bloomberg last year, in which the company (a rival to Thomson Reuters) incorporated Tweets related to specific companies in a wider data stream.

Here, the Thomson Reuters implementation goes one step further by then creating visualizations and charts based on this kind of data — one of these is illustrated above. Looking at the graphics, traders and other Eikon users then will be able to look further into the data to track specific Tweets, people and companies on Twitter. (To be clear, Bloomberg has enhanced its basic service since launching it and also offers some visualisation ability now, too.)

“We aren’t revealing exactly which services we use but we are combining a weighted list of what we consider to be industry influencers with all StockTwits (people Tweeting using cashtags related to global stock markets) and also a cross-twitter feed that provides us with a significant sample of all Tweets across the world to give us the volumes needed to make patterns meaningful,” the spokesperson tells me.

While Thomson Reuters doesn’t disclose what third parties may be involved in its rollout, the types of companies that are sitting in between Twitter and customer-facing enterprises like Thomson Reuters include the likes of Datasift, which mines and helps structure data from social networks like Twitter through the use of metatags.

For now, the sentiment analysis uses only Twitter, but Thomson Reuters is working on adding more content sources, including blogs, in the future.

Thomson Reuters believes it is the first mainstream financial platform to provide twitter sentiment in this way “on a broad scale.” Eikon has some 120,000 people using the service on desktop, “and that grows exponentially every week.” That’s a turn of events from a few years ago, when Thomson Reuters was still sweating out the billion-dollar investment it had made into the development of Eikon as a way to better compete against Bloomberg.

With the SEC last year formally acknowledging that companies can communicate news legitimately via Twitter (as long as investors are alerted of it), Twitter has become an increasingly central part of the conversation around how different businesses and industries are progressing.

But for those of us who have already been using Twitter as a news source, it’s surprising that it’s taken this long for the financial industry to come around to figuring out how to do this more formally. Thomson Reuters itself acknowledges that some “50% of quantitative firms are now using machine readable news feeds,” citing research from the Aite Group. But as with other examples in the big data space, in many cases a lot of that data is not easily usable for non-technical people — traders being the specific people in question here.

“Behavioral finance is an area of increasing interest in financial markets. However it has been difficult for human traders to keep pace due to the sheer volume and detail of data and the need to interpret it and spot trends immediately,” said Philip Brittan, chief technology officer and global head of platform for Financial and Risk, Thomson Reuters, in a statement. “With the addition of this sentiment data to Eikon we are combining our unique content and insight with innovative visualization and analytics tools. This is really just the tip of the iceberg in terms of what we plan to do to turn qualitative, unstructured text into quantitative and actionable insight for our customers.”

Other vertical deals announced that mine Twitter data for bigger-pictures of consumer usage and trends include a deal with 300 Entertainment for music insights; and deal with Dataminr and CNN to mine Twitter for breaking news, aimed at newsrooms worldwide (not just those of CNN itself).