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You've probably heard of sentiment analysis, a technique that allows computers to determine whether a comment is positive or negative about a subject. You can probably imagine a few uses for this kind of technology, such as culling social media for mentions of your brand, but you might be surprised about how much effort Google is putting into this area, including recently purchasing a startup that specializes in sentiment analysis.
Google has already made public its use of sentiment analysis for organic search. You should see its use of this technique only increase.
If you think about the way search ranking algorithms work, there are only two areas that matter: what happens on the page and what happens off the page. The on-page factors— how many instances of the search keyword appear on the page or whether they are in the title or just the body of the page—are easily gamed by spammers. They are still important, but for competitive keywords, they've never been enough. You've always had to win the off-page game, which has traditionally been about the number and quality of links to your page.
Image via CrunchBase
There are a few problems with this approach, as successful as it has been for Google. One is that even links can be gamed, through link farms, comment spam, paid links, and many other techniques. Google has spent years battling that problem and is increasingly using other factors in addition to links to determine the quality of the page, including social media activity.
But one problem with all of these popularity techniques is that people sometimes talk about you because they hate you. And it doesn't make sense that Google ought to rank your page higher if you are hated, at least not in all circumstances. For that reason, Google is working more and more with sentiment analysis, so that they can know a bit more about the tone of each link and each social media mention.
Simple sentiment analysis uses the lexicon—the words used—to determine which statements are positive and negative, but it isn't all that accurate. Much of the time, we speak in sarcasm ("That movie was a great use of my time") or we don't use any telltale words in our opinion ("This is the Edsel of cell phones"), so smarter techniques use machine learning to match up a small set of human-coded correct answers to determine patterns (perhaps that the word "Edsel" is almost always part of a negative statement).
Google will undoubtedly have many uses for highly accurate sentiment analysis (Google Alerts that highlight negative comments?) but they continue to try to figure out what makes a high quality page, so sentiment analysis will be a growing part of search.
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Mike is an expert in search marketing, search technology, publishing, Web personalization, and Web metrics, who regularly makes speaking appearances.
Mike's previous appearances include Search Engine Strategies, AD:TECH, Consumer Reports WebWatch, OMMA East, and the Enterprise Search Summit.
Mike also writes the Biznology newsletter and blog, is the co-author of the best-selling Search Engine Marketing, Inc., and writes the search marketing column for Revenue Magazine.
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