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IEEE Spectrum notes three new patent applications from Google that suggest how Google hopes to improve targeting for social media advertising:

The patents—Open Profile Content Identification, Custodian Based Content Identification, and Related Entity Content Identification—and the algorithms behind them would let Google find patterns in users’ profiles, pages, and friend lists in order to better target ads to them. Ideally, they would make the users more likely to click through.

Google’s Related Entity patent, for one, involves prying information from a user’s list of friends or user groups. But Google is not alone in this field. In June the social ad firm SocialMedia Networks said it had invented an algorithm called FriendRank that also scours a user’s friendship lists for friends whose names might be dropped in a targeted ad.

The Open Profile and Custodian patents would mine data from, say, a MySpace user’s profile and the profile of the MySpace page the user is visiting. The Open Profile patent, for instance, would consider a user profile like “I really enjoy hiking, especially long hikes when you can camp out for a few days. Indoor activities don’t interest me at all, and I really don’t like boring outdoor activities like gardening.”

Using smart language-processing algorithms to detect the user’s sentiments (“enjoy” or “don’t like” near “hiking” or “gardening”) and other linguistic cues, the system would then potentially serve up active outdoor sports-related ads to this user but avoid ads about more hobbyist-oriented activities.

Google is continuing to apply the adsense paradigm of contextual targeting, but expanding the definition of “context” to include the friend networks and the declarations of interests that are common to social network profile pages. MySpace’s hypertargeting is a similar approach.

Facebook’s engagement ads are a markedly different approach, charging for actions rather than using targeting to lift CPMs within display advertising. I think engagement ads could be a very interesting approach that takes advantage of the native behavior of “user affiliation” withing social networks.

I’m indifferent to which standard wins, but I do want a standard to emerge. We need a standard in social media advertising to unlock further scalable growth in this industry.

  • afhill

    I’m really surprised that more folks are not up in arms about these patents, and the privacy concerns. I mean, Google got their hand slapped with Google Flu Trends, that potentially individuals could be identified by their search terms. What these patents represent appears much more concerning to me.

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  • Alex

    I think there’s a better way to achieve what google is trying to do w/out “computing” its way of reaching people. When people write about their likes and dislikes does make some assumptions that people know what they’re talking about. For example, “I like hiking”, perhaps the person meant to say they like hiking in Antartica or they may have tense issues and really meant “I liked hiking” — remember, people are posting in a social context so we all put our best foot forward and keep things ambiguous and in the present tense.

    I like hiking but since I damaged my ACL, I can’t hike effectively and lost interest in hiking but doesn’t mean I don’t like to hike.

    Well, if Google can build this intelligence then what a great idea, I sense a great more logic will be interpeted, mined and post-processed than what I’m thinking I guess.

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  • http://board-exam-review.blogspot.com Board Exam Review

    Why doesn’t Google just base the ads on the individual’s personality and preferences? These patents are too hard to understand.