The Web Has Feelings Too: How Seattle Startups Are Cashing In on Sentiment Analysis

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really is. Philip Vaughn, co-founder of the Seattle-area startup Raveable, has some valuable perspective. Raveable is a travel website that summarizes the sentiment of hotel user reviews. As Vaughn explains, there are three different technical approaches involved in these various companies: making sense of opinions (sentiment analysis), classifying topics (what is a statement about), and mapping relationships (who else has similar sentiment). “From a business perspective, there is an opportunity to do [things] on a scale never before possible,” he says.

An earlier conversation with Vaughn convinced me that understanding the sentiment of a sentence where the computer doesn’t know the exact context or topic—hotel rooms, say, or doctors in hospitals—is still too difficult for today’s commercial software (indeed this can be hard for a person too). It’s a deep research problem in artificial intelligence and machine learning, and many groups are working on it. “Broad sentiment typically has lower accuracy than topic-based sentiment analysis,” Vaughn says.

But, for certain targeted business applications, sentiment analysis has clearly found a home—especially when packaged with other customer-focused products. Take Appature and the healthcare market. “From what we’ve seen of other offerings, they do a good job of giving you sentiment around social media based on keywords,” Shahani says. “But it is not integrated with the broader set of data a company has about their customer. In many cases that satisfies the need, but our customers are looking to leverage social media in a much more actionable and relevant way.”

On that thought, the granddaddy of local “sentimental” startups (my usage, not theirs) is probably Bellevue, WA-based Visible Technologies. Founded in 2003, Visible takes all of this a step further in another direction: reputation management for brands, products, and people. Back in June, the company released TruReputation, a software product that expands on what Visible is already known for—namely monitoring the Web for buzz about a particular brand or company, and helping marketers respond to it. The latest software finds positive and negative content about a brand online, say, and uses keyword placement, optimization, and linking techniques to make the positive entries pop up higher in search results (on Google, Bing, Yahoo, and AOL Search). How exactly it does this is a company secret, but Visible has certainly been getting a lot of interest.

So where is all of this headed? The business applications of sentiment analysis are clearly taking off in certain targeted marketplaces, and the Seattle area has become a leader in the space. Beyond that, the effort to make sense of greater and greater reams of data will continue, but semantic technology needs to improve before we’ll see it everywhere.

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Gregory T. Huang is Xconomy's Editor in Chief. E-mail him at gthuang [at] Follow @gthuang

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4 responses to “The Web Has Feelings Too: How Seattle Startups Are Cashing In on Sentiment Analysis”

  1. Gregory, I can imagine that, from among the companies you identify, a set of tools or protocols are going to emerge that will become second nature to doing business and managing a brand/reputation. I wonder, though, if part of what is happening with the new kind of social networking is going to end up so deeply personalizing communications, that companies are not going to be able to so much “manage” or manipulate reputations as they are simply going to have to deploy, into the stream, their flesh and blood employees and representatives, and let them speak, and just live and die with the quality and authenticity of who embodies the corporate/brand culture.

  2. Gregory T. HuangGregory T. Huang says:

    William, that’s an interesting point. My feeling is it’s already happening–companies will always strive to manage their brand reputations using whatever tools are most effective (flesh and blood employees are still the best).

    Also, Bryce Baril from MarketOutsider wrote in to say: “If I were to contribute anything to the theme it would be to agree with what Vaughn had to say. We find it is much easier when you can focus on a single topic, as they all have their own tones and lexicons. The other thing we’ve found is at a per article- or author-level sentiment analysis can be starkly wrong, but when looked at in aggregate it tends to be rather accurate.”