When a well respected, global information service provider gives the nod to sentiment analysis, you've got to sit up and take notice. I know I sure did when I read that Thomson Reuters has begun offering a sentiment scoring service for social media as an extension to its machine-readable news offering.
Consider the service, called Thomson Reuters News Analytics (TRNA), as a testament to how far we've seen social media expand beyond its original "what's up, where I am, what I like" personal use. Social media's impact is not lost on the financial markets, which have seen "a dramatic rise in the volume and influence of industry blogs, social-networking and commentary Websites," Thomson Reuters noted in a press release announcing the service.
"Investment firms are embracing new data, tools and techniques to help make sense of the massive amounts of unstructured data available on the Internet," said Rich Brown, head of quantitative and event-driven trading solutions at Thomson Reuters, in an official statement. "When properly analyzed and understood, this data can complement a firm's trading and investment strategies and give it a competitive edge.
"This launch will give investors additional capabilities to gauge stock, sector, and market sentiment, and to translate these emerging sources of market insight into data that can be incorporated into both quantitative strategies and as a way to provide a broader context to human analysts."
In other words, this isn't just about reading the news any longer. It's about interpreting it.
Thomson Reuters' machine-readable historical and structured news feeds typically integrate with algorithmic trading systems plus risk management and decision management systems. Now, with TRNA along for the ride, comes "sentiment, relevance, and novelty indicators that capture market opinion," the company says.
For the service, Thomson Reuters uses information delivered by Moreover Technologies, an aggregator of global news and social media. News Analytics provides access to as many as 50,000 news sites and 4 million social media sites. It's available for deployment or via Elektron, Thomsom Reuters' hosted high-performance data and trading infrastructure.
The TRNA engine, powered by Lexalytics text analytics technology,
can scan and analyze stories on thousands of companies in real-time and make the results available for quantitative processes. The result, Thomson Reuters notes, is "buy/hold/sell signals within milliseconds."
Plus, it promises, the service will track news sentiment over time for broader, historical perspective on a company's market reputation.
As investment firms and other financial companies seek ways to account for social sentiments in their analysis, having a known player in their corner will no doubt give them some much needed comfort. Wouldn't you agree?
Actually, Lyndon, I think if Thomson Reuters marketed the service using its credibility as the main branding that would be another matter. Instead, the announcement seems to focus on the number of news sources available. Competing on quality of content versus quantity is the key.
I'm not suggesting the tool is invalid even if it is just an effort by Tompson Reuters to develop their own proprietary sentiment analytics tool. I'm only questioning whether it represents any big leap forward.
I'd tend to think TRNA would have a bit of an edge, both actually and in terms of public perception. One would think that business news journalists and analysts, who presumably spend their daily professional lives sifting through megatonnes of information from worldwide sources, would be valuable resources to help the analytics wizards refine all their parsing and analytical algorithms, incorporating stuff like the relative reliability/credibility of the vast global assortment of sources.
My point exactly. I'm not certain how the adoption of sentiment analytics by a "trusted" information provider suddenly removes all the stigma surrounding the techniques. I'm not necessarily down on the use of sentiment analytics, only on the idea that a technique should be embraced or discarded based on who is using it.
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