Data, Methods, and Ethics

First Data Set:

To collect my first set of data, I looked at the "formspring" accounts of three females and three males, ages 16-18, everyday for a two week period (May 10, 2011- May 24, 2011).  I looked at every post for two weeks and decided if the post was positive, negative, or neutral.  

I coded the data using the following guidelines:

Positive: Any comment complimenting the user or using positive words

Example: "You looked hot in those prom pictures"

Negative: Any derogatory comment toward the user or any person

Example: "Ur face looks like it got hit by a baseball bat"

Neutral: Any comment asking a question that is neither negative or complimentary. 

Example: "What color is your car?"

I chose this data because I wanted to see if people in the 16-18 year old age group were posting negatively or positively in an anonymous setting.

I did not ask for informed consent because the posts were public.  I did not use any names or personal information.

Second Data Set:

To collect my second set of data, I looked at the posts on "collegeacb.com" in the Santa Clara University section.  I used all posts.  I looked at both the questions posted and the replies.  I then decided if the original posts and the replies (separately) were positive, negative, or neutral. 

I coded the original posts using the following guidelines:

Positive: Any post speaking positively about a group or person.

Example: "Joe Smith*...quite a nice guy"

Negative: Any post speaking negatively about a group or person.

Example: "Tri Delta* is weird: So i was just at tridelta* and i felt like i had to report how it was...bunch of creepy guys there haha i feel like tridelts* are all creepy"

Neutral: Any post asking a question.

Example: "Engineering School"

*changed name

I chose this data because I was interested in seeing if college aged students were asking positive or negative questions in an anonymous setting.

I did not ask for informed consent because the posts were public.  I did not use any names or personal information for my analysis of the data.

I coded the replies to the original posts using the following guidelines:

Positive: Any reply speaking positively to the original post or about someone.

Example: "Don't hate, she is a nice girl."

Negative: Any reply speaking negatively to the person who posted or the topic of the post.

Example: "The 'point' of them is for those kids who can't make friends normally so they have to pay a ridiculous amount of money to buy some friends."

Neutral: Any reply talking about a different topic or asking a question.

Example: "What about Kappa?"

Third Data Set:

To collect my third set of data, I looked at "postsecret.com" everyday for two weeks (May 10, 2011- May 24, 2011).  I decided if each post was positive, negative, or neutral.

I coded the data using the following guidelines:

Positive: Any post showing happiness or excitement.

Example: "THIS WEEKEND WAS MORE FUN THAN I THOUGHT WAS POSSIBLE IN ADULTHOOD."

Negative: Any derogatory post or a post that showed sadness or pain.

Example: "YOU ARE NOT A schizophrenic.  You've just done A FUCK TON of drugs.  Get it right."

Neutral: Any post that was neither positive or negative.

Example: "I am a journalist and I am commenting on my own articles."

I did not ask for informed consent because the posts were public.  I did not use any names or personal information.

I chose this data because I wanted to see if people of all ages were sharing negative or positive secrets anonymously with complete strangers.