Software Salariman

If you read Usenet newsgroups, no doubt you'd be familiar with spam messages spruiking credit, fake jewellery, external organ enlargements and free graduate degrees. On a PC, you can use killfiles in newsreading software to ignore spam messages. If you're reading newsgroups using the Google Groups web-based reader with Firefox, you can ignore annoying spam messages using a Greasemonkey script called Google Groups Killfile (GGK).

You can add entries to your killfile list using GGK's context menu but the list becomes hard to view and manage once you have a lot of entries. It is easier to edit GGK's kill list variable:

• Enter "about:config" in Firefox's location bar.
• Enter "kill" in the Filter field.
• Click on greasemonkey.scriptvals.www.penney.org/Google Groups Killfile.GoogleKillFile and edit the configuration string.

2008-04-14: If you use regular expressions (RE), you can reduce the number of entries in the killfile list by using wildcards and the "alternate" operator (vertical bar symbol ("|")). You can further reduce the number of patterns to define by specifying case-insensitive comparison in GGK. Just search for the REs' "compile()" function in the GGK script and add a second "i" argument.

Labels: Firefox, Google, Spam

My e-mail spam detector, SpamBayes, seems to have problems classifying some of this year's spam, placing two or three in the Suspect folder each day when there used to be none. The main culprits are stock market e-mail, probably because their content includes a lot of business-oriented words (hard to avoid at work) that outnumber the relatively small proportion of definite spam words. Lowering the spam threshold works well enough; what really matters is that ham e-mail still gets ranked at 0%.

Labels: Spam

After trying Outlook 2003's spam detector for two weeks on my new notebook, I turned it off because it was still leaving spam in my inbox. Outlook's spam detector would even leave e-mail that had been classified with "{Spam}" in the subject by my corporate e-mail filter! I've installed SpamBayes again and look forward to a clean inbox in the near future.

Labels: Spam

After running SpamBayes in addition to our server-based spam filter for one week, my inbox is spam free! It's so-o-o much nicer to start the day and see spam getting clobbered.

Labels: Spam

While browsing the spam tokens reported by SpamBayes, I realised that spam messages often have the same words, including typos and deliberate mispellings. As described in Paul Graham's A Plan For Spam, it's pretty straightforward to detect spam once you have trained your spam filter. Spammers are victims of their own dubious success; the more spam they send, the more duplicates each person is likely to receive and hence identify automatically as spam. Unfortunately, not everyone knows how to run their own spam filter. Heck, I've been online for years but only just started my own filter.

Julian asked why spammers think anyone would buy mortgages / fake watches / online diplomas / genital enhancements / medicines from a stranger based on a tacky and badly spelt message. Other than the obvious response that enough fools actually respond to spam to keep spammers employed, perhaps enough people accidently click on the spammer's link to earn them advertising dollars!

Labels: Spam

You'd be a lucky person if you don't receive spam e-mail. I get about 15 spam e-mail daily, which is a smallish number but annoying. My company's mail server identifies about two-thirds of spam e-mail correctly, leaving me to deal with the remaining third. This is a pain but I can see our IT administrator's point of view; he can't really make his filter more aggressive without mis-identifying valid e-mail as spam. So, I looked around for a personal spam filter and found SpamBayes. It's a Python program wrapped within an Outlook plug-in, and delivered in a Windows installer, so it's pretty easy to install and use. I'm looking forward to seeing some results tomorrow!

Labels: Spam