Speeling erroes kil blogers kredibilty (in the wild)
From the article:
“The company [goosegrade.com] asked a demographically diverse group of respondents on Amazon’s Mechanical Turk website to fill out the survey and published the results today on the goosegrade.com company blog. The bulk of respondents spent some time reading blogs but were people who remained dependent on ‘mainstream sources’ for most of their news.”
(For an explanation of Mechanical Turk, the Wikipedia article is here.
Comment: How does goosegrade know these people were demographically diverse? The only people they asked were Mechanical Turk workers. That seems like a very specific group of people. So you should only be able to make inference about that group of people. They hardly speak for internet users in general, but goosegrade.com uses them to make inference about “internet users” when they should just be making inference about “mechanical turk workers who are being paid by gooseGrade.com”. Those two groups are drastically different.
gooseGrade.com says on their site (http://www.goosegrade.com/reader-perception-survey-results)
“Readers want gooseGrade. Here’s proof.
175 People polled.
ABSTRACT: It appears that grammar, spelling, factual, and other errors do affect reader opinion as well as how likely they are to share or link to an article. These errors also seem to dictate the readers opinion of the author’s skills as a writer. 65.86% of internet users say that a tool like gooseGrade would increase their confidence in the content they are reading. Filtering further shows that 9 out of 10 newspaper readers say that a tool like gooseGrade would increase their confidence in author’s content. This merrits further investigation of newspaper readers and could show a path for new media to take more market share.”
As I said before, I’m not sure the opinions of 175 (more on this below) mechanical turk workers are sufficient to make inference on all internet users. Furthermore, remember that all of these respondents were paid by goosegrade.com (although it was probably only a few cents.)
A note on their sample size: They claim a sample size of 175 internet users, but an examination of the raw data shows that there are only 161 unique IP address. 9 IP addresses are repeated twice and 1 IP address is repeated 5 times. These should be thrown out of the sample because it is likely that they are the same person.
The readwriteweb.com article concludes with:
“Below are a few of the charts, you can see the rest on the GooseGrade blog. The lesson here? It seems pretty clear. We bloggers are harming our own credibility and traffic with our inattention to details, not just in the facts, but in the basics of our writing. Let’s do better!”
Here is a promise I am willing to make. I’ll write better and make less grammatical errors if you apply statistics more fairer. (LOL)