If content filtering exists in America, there ought to be a way to prove it one way or the other. Any experiment should be open to the public with all assumptions identified and the experiment should be reproducible and have a scientific evaluation criteria.

As a working assumption, there should be three elements to the number of site visitors when averaged over time. First, there should be some measure or regular visitors who would average out over time to some relatively constant value. Next there should be a feed from the search engines which is a factor of the public interest in your topic. Also, there could be a viral effect where visitors recommend you to others and therefore one site visit by Google referral or one regular visit may translate into any number of visits. (This is probably highest with jokes and politics and lowest with technical). However, if both groups (regulars and referrals from Google) recommend you to about the same number of people, this doesn’t alter the mathematical approach.

For the past three weeks, this site has varied around 41 to 87 visitors a day with an average around 60 a day but WordPress only holds the search engine data for a week. So I have the following Google Data and site visitors.

Google Referrals—–Visitors

44——————53

51——————67

44——————64

48——————62

50——————75

33——————48

40——————54

Now I ran the above data through an online Linear regression tool and came up with a very high correlation coefficient of 86% (R squared 75%). For a moment just think of a fat reduction pill where the weight you lost was 75% related to the pills you took and independent of all other variables like food and alcohol consumption and exercise or other variables.

The equation is **visitors equals 1.3(Google Referrals) plus 4.1(regulars)**

Obviously no viral effect and a small number of regular visitors, but if you need the technical information you come because of a Google search.

Now the data is drifting down because the site has not been very active for the month but the average for the data above is 60 with a two standard deviation range of 42 to 78. I would be hard pressed to make a case for effective **Content Filtering** based on this data set because there is no sharp break in the curve and the number of visitors for the past week is much the same as it’s been for the past three weeks.

Just for fun, I have two very dormant sites one in business (2.6 visitors a day) and the other in recreation (5.4 visitors a day). The equations and correlations are as follows:

**visitors equals 1.4(Google Referrals) plus NO(regulars)** correlation coefficient 95%

**visitors equals 1.0(Google Referrals) plus 1.8(regulars)** correlation coefficient 89%

Once again there is no sign of content filtering as the sites just suffer from a lack of interest, both mine in writing on the topic and visitors needing information on the topic.

Content filtering is an on-off switch which is turned on when the content gets out of hand so there should be signs of a dramatic drop in traffic.

At Fatsavage.wordpresss.com I have seen three cases of dramatic content filtering over the past 6 months with two in the past month. Start reading at the home page and work backwards to December 18, 2007. In that short month (about 12 posts), I managed to piss of the Feds twice and been slammed by provable content filtering. Now, I was attempting to be offensive with all of it, but I failed 10 times as only two posts were serious enough to get blocked.

Can you figure out which two?