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Future gazing: A Recorded Future timeline shows the dates of future product launches, as well as previous releases.

“We have proven out that our data can make strong predictions,” says Ahlberg, citing studies that compared Recorded Future’s output with changes in the volume of activity around particular financial stocks. “We found that our momentum metric, which indicates the strength of activity around an event or entity, and our future events correlate with the volume of market activity,” says Ahlberg.

His company’s tools can also be used to work out which sources of information give the best clues as to future events. A recent analysis showed that the posts on one of the Financial Times blogs were better than other news sources at predicting the performance of companies on the S&P 500 share index. Negative posts about a company correlated with below-market performance a week later, while positive ones correlated with above-market performance.

“What they’re really doing here is identifying and collating statements that have been made about the future,” says Steven Skiena, a computer scientist at Stony Brook University in New York. Skiena developed similar technology used by another startup, General Sentiment, to mine material from news and blogs. “An analyst can use those to inform their own predictions, less risky than Recorded Future actually making predictions themselves,” he says.

Various tools are capable of extracting events, people, and companies from text, but aligning that information in time is a trickier task, says Panagiotis Ipeirotis, an associate professor of information, operations, and management sciences at New York University’s Leonard Stern School of Business. Ipeirotis researches how economically important data can be mined from online news sources and social media. “Analysis of sequences of events is very interesting, and underexploited in the research literature,” he says. “Even getting decently timed data of news articles in order to properly generate event sequences is a hard problem.”

This focus on the time line sets Recorded Future apart from other firms trying to gain insights by mining news and other data, says Ipeirotis. “I’m curious to see when other text analytics firms will jump into the trend.”

Recorded Future is about to expand its service to cover Arabic and Chinese sources. Making its indexes bigger is a major priority. “I’d like to be able to get in front of every piece of streaming data on the planet,” says Ahlberg.

As the databases covered by Recorded Future, General Sentiment, and others grow, more powerful types of analysis will become possible, says Skiena. “I’m currently working with social scientists on models to predict what the probability is that a person that gets few mentions today suddenly becomes very famous in the future, by looking back at years of past data,” he says.

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Credits: Recorded Future

Tagged: Business, Web, Google, search, startups, Web, predictive software, natural language

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