Keyword Spamming YouTube

Google is being exploited by spammers on Google video and YouTube. When they start paying for content it will only get worse! Jeremy wrote a little rebuttle of a MyBlogLog spammer, cornwall seo talks about it too and browsing google video directly after that I started seeing the same there.

I am a big fan of NCIS... I can't help it I like the humour coupled with the overwhelming sense of coolness and fairly decent plots. Very quickly since google video integrated YouTube listings into it's search results (great quick exploitation of synergy there well done G men + women) I realised that all my fave shows were now being offered up as bootleg copies:

This in itself isn't the end of the world since it costs $1.99 to get the CBS version and I can keep it on my machine easily and (thankfully) don't have to get up every 10min to move onto the next clip but it led me to test out a theory on another nasty spam technique I used to use in my early days of SEO (which timed with Napster). Keyword stuffing...

On this page you can see a search for NCIS turns up Gilmore Girls and South Park (page 2 of results). You can also see that the descriptions are keyword stuffed with "ER", "CSI" and various other popular TV shows.

The joy of using back links to help determine the keywords a web page is valuable for in Natural Search means you can devalue the keywords on the page (to some extent) or at least get a hint to pick the most relevant ones. Combine this with the fact that (excepting cloaking) the page has to be user readable it's not too hard to see why keyword stuffing doesn't work for webpages any more. I however rarely read the descriptions of the YouTube and G Video's I watch and so spamming the description isn't going to hurt me. Combine that with the fact all Google has to go on is title, description, #times viewed and a little bit about the uploader I think we are coming to an interesting challenge for Google to deal with, similar to Jeremy's mybloglog problem and eBay's keyword stuffing problem in search results.

Good luck Google... get your brains on it (and get your users tagging that content ;) )!

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I am trying to understand how Amazon's SIP and Yahoo's Term Extraction
features are implemented. I'd like to find an algorithm with no
training requirements, preferably statistical and amenable to
near-real-time execution. A python implementation would be nice.