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There’s a new Guide to Social Media Analysis recently published by Nathan Gilliatt of Social Target, who blogs at http://net-savvy.com/executive/. This guide is hefty, and includes 31 profiles of a wide variety of companies (including Collective Intellect) that offer services related to social media monitoring, analysis and consulting. You can read more about it here and purchase your very own copy here.
Algorithms — problem-solving programs based on mathematical formulas — are making it easier for investors to filter the massive amount of text produced by news wires, newspapers, industry journals, clinical studies and legal filings for kernels of information, and trade on them in the blink of an eye.
Though the expanding array of news on non-traditional media like blogs and chat pages is a challenge for the robot readers, the speed and efficiency offered by news-mining algorithms are helping hedge funds with just a handful of staff generate as many trades as a giant investment bank and becoming a potential boon to the media industry.
“This is a new class of information technology,” said John Partridge, vice president of industry solutions with StreamBase Systems, a technology provider that specializes in processing and analyzing real-time streaming data.
High-frequency investors such as hedge funds are using news-mining platforms like those offered by StreamBase to troll through thousands of electronic feeds of streaming text to identify key phrases on which to trade.
Popular phrases include “lowers its outlook” or “raises guidance” or even buzzwords like “stellar performance” that could potentially push a stock lower or higher.
Hedge funds, with their rapid-fire trading style, often allow the news-mining platforms to make trades on their own, capitalizing on the technology’s speed
However, longer-term investors are less interested in flooding the market with orders after a particular headline. They are using the platforms to keep track of developments that may affect companies in their portfolios or influence their strategies, technology developers said.
News mining is not just for stock trading, either. For example, French investment bank BNP Paribas’ “weakness indicator” counts the number of times the words weak, weakness or weakening are used in the Federal Reserve’s beige book report on regional U.S. economies.
More than 50 references in a report typically signals the economy is on the brink of a recession.
Hedge fund investors familiar with news-mining technology said an algorithm based on the “weakness indicator” could easily be created to sell dollars and U.S. stocks and buy bonds if more than 50 references were found.
“What the machine is looking for is the same thing that the human is looking for. It can just find it more quickly,” said Richard Brown, business manager of NewsScope, a company owned by Reuters Group that produces machine-readable news.
Rather than just highlight words or phrases, some of the most sophisticated news-mining platforms can take multiple strands of news from wire agencies and websites and score the significance of various items.
For example, headlines from a reputable news organization with the words “Middle East,” “tension” and “hostility” would be given a higher score, especially if oil prices are rising, than an anonymous blog entry with the same key words.
The same headlines would be given an even higher score if other reputable news agencies carried similar stories.
“A lot of times, the content that’s important is not in a single article or document,” said David Leinweber, a financial technology consultant with Leinweber & Co. “the idea of considering individual news stories only as atomic events misses some things,” he said.
On his own blog ” Nerds on Wall Street,” Leinweber noted the example of Accentia, a pharmaceutical company whose share price shot up 70% one morning in October 2006 after the successful trial of a human cancer vaccine was announced in a press release.
However, the press release was based on an article from a medical journal published a month earlier. Also, local press in St. Louis, where Accentia has a plant, reported on the testing a week before the press release, and a blog for patients discussed the drug days before the stock jump.
An investor using news-mining technology could have been buying into the company days, if not weeks, before the big share price rise.
Computers, however, are not perfect when it comes to reading the various forms of language in both standard and non-standard media.
Consultant Leinweber added that machines often have difficulty with subtle double negatives and vague pronouns that human readers can understand easily with context.
For example, machines could potentially stumble when it comes to a sentence such as: “The company’s chief executive said he did not dislike the way that that product sold well there.” A person could scan the sentence and understand it.
The growing amount of text and information available on blogs, chat rooms and online forums also pose challenges to robot readers.
“That’s one of the limitations. When you look at chat room and blog content, it’s the emoticons, it’s the profanity, it’s sarcasm or all caps,” said NewsScope’s Brown.
Still there is growing interest in the investment community in being able harness the information available in so-called social media.
Darren Kelly, senior vice president at Collective Intellect, a company that specializes in filtering and ranking media content, said blogs and online forums can provide a unique window on sentiment surrounding an issue or a stock.
“The usual multiscreen setup that everyone has used in finance for the last 20 years no longer gives them all the information that’s available,” Kelly said.
I’m heading to two conferences this weekend in the San Francisco area. The first is @ Supernova2007. SuperNova is advertised as:
Business, technology, and social interactions are decentralizing, tearing apart industries with the force of a supernova. Intelligence is moving to the edges, through networked computers, empowered users, fluid digital content, distributed work teams, and powerful communications devices. Business models are under pressure as end-users gain greater control, computing becomes a commodity, and companies collaborate across geographic boundaries. At the same time, new opportunities are emerging through social software, pervasive wireless networking, massively multi-player virtual worlds, and distributed e-commerce, among other trends.
Sounds like fairly heady stuff right? I certainly hope so and will be looking to connect with a few of the thought leaders out there including Paul Kedrosky, Lada Adamic (an advisor for CI), Julie Hanna Farris, Udi Manber, and others. The second is Foo Camp 2007 sponsored by O’reilly. This is an invite only event sent out to thought leaders on the web. One of my heros, Paul Graham, who turned me on to Ruby in his book “hackers and painters” will be there and am greatly looking forward to the dialog. The agenda is worked out by the attendees on Friday evening and everyone literally camps out on the O’Reilly campus at night. Should be very interesting times.
My last company was coined as Business Activity Monitoring or BAM by Gartner, the sages of Information Technology almost a year after we started. The current business that I founded in 2005 could use some naming standards as well. There are a lot of companies out there touching various aspects of this market that label themselves as Buzz Monitoring or WOM (word of mouth) monitoring or Vertical Search or Competitive Intelligence or Media Tracking or Brand Monitoring or Knowledge Management 2.0 or blah blah blah. Driving a standard naming convention removes the veil of market confusion driven by fragmented marketing messages. So, Gartner, Forrester, IDC and others if you are listening let’s not wedge this area into one of the existing boxes. Also, this is much bigger than just calling it Buzz Monitoring. Instead, let’s call it Media Activity Monitoring (tada, trumpets and such).
Media Activity Monitoring covers:
