Paul Graham, A Plan for Spam

Fri, 16 Aug 2002 12:03:14 +0000

Paul Graham, A Plan for Spam.

I used spamassassin for a while, but removed it temporarily when it started eating my computer after being reintroduced to 200 emails at once when I’d been away from the net. And I haven’t replaced it since, because I quite quickly realised that with an approximate 20:1 spam to real mail ratio after filtering out mailing list stuff, it’s actually simpler to delete spam from the inbox by hand these days than it is to check the spam folder for false positives (which may be a couple of orders of magnitude rarer, and so much easier to miss). So, I don’t have any filtering any more.

Probabilities better than scores? As raph pointed out, you can take logs to the probabilities and get scores, but I don’t think that’s the issue. The interesting point is how you arrive at the per-word numbers in the first place, and the advantage of the Bayesian system is that it’s transparent. Assuming current styles of email communication, I doubt that you will see Paul Graham’s webmail system decide that a valid signature delimiter is an indicator of potential spam.

But on a more general note, I think that Paul’s “Defining spam” appendix is a pretty good indication that we have terminology problems. What he’s built is not in itself a spam filter, it’s an uninteresting-mail filter – actually a far more useful tool - and if he were to refer to it as such, a lot of the borderline cases go away. Domain renewals are interesting to me: offers from Verisign for a Free E-Commerce Web Site are not. It doesn’t matter if they think I’ve opted in or if I have an existing relationship with them: the point is that I don’t want it, and I don’t need to define it as spam before deciding to filter it.

I define spam as persistent or large scale sending of email in which there is no reasonable expectation that the recipients will be interested.

This is not a good definition for computers to use; they tend to choke on words like `reasonable’ – but that doesn’t matter. Computers on the receiving end are just filtering for interestingness anyway and don’t need to care if it’s spam. Computers in the network are primarily concerned with abuse of the net, so they don’t need to care if it’s spam either. If it’s relaying through my servers, or faking its origin, that’s a good enough reason to stop it no matter what the message content.

Use of automation is a characteristic of much spam, but it’s not essential or even exclusive. Suppose someone at Amazon has determined from reading my web pages that I like the Propellerheads, and sent me email to say that they have the new album at half price. That’s welcome news to me, and it makes no difference whether they sent the same email to a million other people (we assume that they’d determined that those other million were equally as interested). On the other hand, you can hand-letter your offer of cheap toner cartridges on vellum with a quill ten thousand times and send me six of the copies (each to slightly different mailboxes which are all too clearly routed to the same eventual destination) by courier delivery, and it still represents the large-scale sending of mail where you clearly made no effort to determine whether the recipients were interested. Spam.

For the record, I don’t want to know about toner cartridges.