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Social Networks Settles Lawsuit Over Phony Friends 127

Hugh Pickens writes "Techflash reports that has agreed to pay up to $9.5 million to its users to settle a lawsuit that accused the social network of sending deceptive emails that made people believe their old friends from high school were reaching out to connect — only to discover, after paying for a membership, that their long-lost buddies were nowhere to be found. Lawyers for the plaintiffs asserted that Classmates had 'profited tremendously from their false or deceptive e-mail subject lines and related marketing tactics.' Under terms of the proposed settlement, members who upgraded to premium memberships after receiving one of the 'guestbook' emails will be able to choose either a $3 cash payout or a $2 credit toward the future purchase or renewal of a membership. is also among companies that have come under scrutiny for their use of 'post-transaction marketing' tactics — in which customers are given additional offers as part of the online payment process, sometimes in such a way that they aren't aware they're also signing up to pay more. A November 2009 US Senate Committee report said Classmates made more than $70 million through its relationship with post-transaction marketing firms. The Classmates Media unit posted $58.8 million in operating profit for 2009, up more than 24 percent from the previous year, making Classmates 'the most profitable social network in the world,' according to CEO Mark Goldston."

Comment Re:linearity (Score 4, Insightful) 108


You understand neither how the parent post is using the word "linear" nor the PageRank algorithm itself. You can rewrite the eigenproblem at the heart of PageRank as the solution to a linear system, but very few people do. Moreover, this is not the correct intuition to employ to understand what's going on: there are no "massive matrix inversions" here, just a simple iterative algorithm for extracting the dominant eigenvector of a matrix.

Furthermore, you've got it exactly backwards regarding the "connection" between PageRank and light transfer. Since the Markov process used to model a web surfer in the PageRank paper is operating on a discrete domain with an easily-calculable transition function, the stationary distribution (or ranking) can be determined exactly. In rendering, you have a continuous problem for which Markov chain Monte Carlo techniques provide one of the most efficient ways to approximate the solution...but you have to actually simulate a Markov chain to get it (see, for instance, Veach's seminal paper on Metropolis Light Transport). Computing PageRank is an "easy" problem, by comparison.

Comment Very (Score 1) 991

A dozen students a year is probably too small to have the depth and breadth you'd want to give you a truly "top-notch" CS education (although a focus on theory is far from a bad thing, seeing as how the undergraduate programs even at top-ranked institutions often skimp far too much in that department).

However, all other things being equal, I might vote for the liberal arts school anyways. Smart people are successful pretty much wherever they go, and the most important thing you'll learn in college is how to think. Memorizing Tomasulo's Algorithm or getting really good at handling templates in C++ are relative wastes of time compared to learning how to apply the scientific method and developing general strategies for thinking critically about complex problems. You could do a lot worse as an undergrad than to get a good exposure to the theoretical underpinnings of computer science, study physics and math really, really hard, and spend the rest of your time learning from people who don't spend all day sitting in front of an LCD screen.

The vast majority of the people I've met who have been truly influential in CS didn't get there by mastering their undergraduate material: they made contributions by looking at problems in ways that wouldn't occur to people who only know what's in the textbooks. Additionally, very, very few of these people have been what I'd call hardcore hackers in a traditional, code-oriented sense.

Good luck!

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