[clug] Cleanfeed. Other Comsequences.

[jm]

There are other methods than pure lists involved. Similar techneques to 
spam filtering can be used, eg, key word or bayesian filters. These are 
more likely responsible for these false positives/negatives. Just try to 
send an email to anyone with the word "free".

Jeff.

Craig Small wrote:
> On Tue, Oct 28, 2008 at 10:13:47AM +1100, Daniel Pittman wrote:
>   
>> The problem is that you are assuming the "false positive" rate is
>> completely randomly distributed; in practice it means that a proportion
>> of sites are completely unavailable despite being innocent, so 3 percent
>> of *websites*, not three percent of *content of all websites*.
>>     
> It is unlikely that mainstream, such as the age or amazon, would get
> blocked. It really depends on where the list comes from.  That's the key
> with a lot of the filters, who decides what is in and what is out.
>
> I know perfectly fine sites that are blocked by Trend Micro, for
> example, not because of any R or X rating, but because they consider
> them "dangerous" because they discuss some of the filters and filtering
> and are critical of them.
>
>  - Craig
>