Who Do Online Advertisers Think You Are?

Image: Edward del Rosario

Image: Edward del Rosario

“Should we worry about ads aimed specifically at us everywhere we go on the Web and, increasingly, on our mobile devices too? Yes, and not just because the ads can be invasive and annoying. Real-time bidding also makes the online marketplace less of an even playing field, allowing companies to send loyalty points or discounts — or price increases — to individuals based on their perceived spending power. The travel site Orbitz, after learning that Mac users spend 30 percent more on hotel rooms than P.C. users, has started to send Mac users ads for hotels that are 11 percent more expensive than the ones that P.C. users are seeing, according to a recent Wall Street Journal article. […]

As our experiences become customized, there is more at stake than just discount coupons and deals. There’s also the future of our common culture. As personalization shapes not only the ads we see and the news we read but also the potential dates we encounter and the Google search results we receive, the possibility of not only shared values but also a shared reality becomes more and more elusive.” (Jeffrey Rosen, NYTimes.com)

Microsoft Builds a Browser for Your Past

Microsoft Builds a Browser for Your Past - Technology Review

Photo: Microsoft Research

“Behind the scenes, Lifebrowser uses several machine-learning techniques to sift through personal data and determine what is important to its owner. When judging photos, Lifebrowser looks at properties of an image file for clues, including whether the file name was modified or the flash had fired. It even examines the contents of a photo using machine-vision algorithms to learn how many people were captured in the image and whether it was taken inside or outdoors. The “session” of photos taken at one time is also considered as a group, for cues such as how long an event was and how frequently photos were taken.” (Tom Simonite, Technology Review)

Algorithm Uses Photo Networks to Reveal Your Hometown

Computer scientists have developed a simple algorithm that accurately guesses your hometown using the location information of photos uploaded to Flickr

Algorithm Uses Photo Networks to Reveal Your Hometown - Technology Review“These guys have studied the geographical clusters of photos that users upload to Flickr, the popular picture sharing website. The task they set themselves is to determine an individual’s home town looking only at the geotags of photographs they have uploaded.

It’s no surprise that people take most of their photographs near their home. But they also take photographs in clusters at other locations such as holiday destinations and such like. That makes the problem of estiamting the home location a little more difficult. The trick that Jahanbakhsh and pals solve is to find an algorithm that can separate the home location from the other clusters.” (KFC, Technology Review)

‘Pre-social network’ finds you friends in your hang-outs

'Pre-social network' finds you friends in your hang-outs

(Image: Forest Woodward/Stone/Getty)

“However, he is concerned that users’ privacy could easily be compromised by such a pre-social network. ‘How would you feel if your future happenstance meetings were all predicted in advance? What if anyone could predict exactly where you will be and who you will be with? It’s a stalker’s dream'” he says.” (New Scientist)

Study finds sites leak user information

“The results of the study showed that the top five recipients of leaked information were comScore, Google Analytics, Quantcast, Google Advertising and Facebook. It also discovered that the top three sites that leaked information were Rotten Tomatoes, CafeMom and LyricsMode. The websites iVillage, LiveJournal and National Geographic were tied for fourth in leaking the most user information.” (The Stanford Daily)