Legend

This page shows a sample of what a user might see after logging in. It is annotated with comments that explain what the various parts of the page mean.

Movie Title

Generic
Hurl Factor

Your Personal
Hurl Prognosis

Your Hurl Reaction

This column lists movies by title

This column displays weighted average generic ratings, as described on the How It Works page, and the generic rating matrix, as described at the bottom of this page.

If you are logged in, this column displays your prognosis (prediction) for certain movies

If you are logged in, this column displays the ratings you have previously submitted and permits you to change them or to submit new ratings. If you are not logged in, this column permits you to submit new ratings.

Movies for which a rating request has been submitted

Cloverfield

Rating Request:
Please rate this movie
if you have seen it

Another user entered this movie into the database to request a rating ASAP. All other users are encouraged to rate it if they have seen it.

Generating a prediction for
this movie is not possible

Movies for which personal predictions are possible

Babel

****
(4)



>>					<<

This movie has a generic rating of two stars. The number in parentheses shows the total number of generic rating submissions for this movie, which includes both generic and nongeneric users.

****
(1)

This user's predicted reaction to this movie is four stars, i.e., it is predicted that this user would submit a rating of four after seeing this movie. The number in parentheses shows the total number of nongeneric users used to generate this prediction.

After seeing this movie, this user can submit a rating for it by using this drop down menu.

Movies for which personal predictions are not possible

Syriana

****
(5)



>>					<<

Generating a prediction for
this movie is not possible

Generating a personal prediction for this movie requires that this user have ratings in common with another user who has already rated this movie. In this case, no such overlap exists.

Movies which you have already rated

The Constant Gardener

****
(9)



>>					<<

You have already
rated this movie

This user has already rated this movie (see the next column). In theory, predictions could be generated for such movies, but the algorithm is a little complicated and hasn't been implemented yet. I'm not convinced it would be particularly useful.

****

Add a New Movie or
Request a Rating For a Movie That Isn't in the Database Yet

(Please don't add a movie that is already in the database, even if there is a typo or other error in the name.
Just rate the movie that is already listed. The administrator will fix minor errors as they arise.)

New movies can be added to the database here, either to submit a new rating or a rating request. However, please heed the request made above with regard to duplicate movie titles. If a movie exists in the database but the title is not quite correct, just rate it anyway. The administrator will fix the error in the title eventually.

Have you read the guidelines before submitting?

Please read the submission guidelines before jumping aboard. Thank you.

Understanding the Generic Rating Matrix

Every generic rating is accompanied by a rating matrix. The first thing to understand is that if you don't want to deal with this level of complexity, you can ignore the matrix completely and judge a movie purely by the generic rating present as a number of stars between one and four. However, if you would like to attempt a more detailed analysis (and subsequent prediction), then the matrix is available.

The matrix is a 4x4 two-dimensional histogram of all the generic ratings submitted for a particular movie. The rows correspond to the four susceptibilities a person can use to describe themselves, and the columns correspond to the ratings submitted for the movie in question. The following examples will help you conceptualize the matrix:

This matrix shows that all generic ratings for this movie came from people who never get motion sick (because the only red cells are in the top row) and that all submitted ratings for this movie were of no motion sickness (because the red cells are in the left column).

This matrix shows that all generic ratings for this movie came from people who get motion sick in movies very easily (because the only red cells are in the bottom row) and that all submitted ratings for this movie were of no motion sickness (because the red cells are in the left column).

The ratings are evenly distributed across susceptibilities and the ratings for this movie are perfectly correlated to susceptibility (people who never get sick reported not getting sick in this movie, people who get sick sometimes reported getting a little sick, and people who always get very sick reported getting extremely sick in this movie).

The matrix can be used in the following manner. First, divide it into four quadrants (effectively 2x2 instead of 4x4). Brightness in each of the four quadrants then represents the following information:

UPPER LEFT A matrix that is bright in this quadrant has only been reported on by people who don't get very sick in the first place, and their reports for this movie are that they didn't get sick.	UPPER RIGHT A matrix that is bright in this quadrant has only been reported on by people who don't get very sick in the first place, but their reports for this movie are that they did get sick in this case.
LOWER LEFT A matrix that is bright in this quadrant has only been reported on by people who tend to get sick in shaky cam movies, but their reports for this movie are that they didn't get sick.	LOWER RIGHT A matrix that is bright in this quadrant has only been reported on by people who tend to get sick in shaky cam movies, and their reports for this movie are that they did get quite sick in this case.

The final point to be made about the matrix is that on a personal ratings page (but not the generic ratings page) one of the rows will be offset by small arrows, like this:



>>					<<

The arrows indicate the susceptibility row that the user in question specified when creating their account. In other words, that is the row which is most likely to represent or predict that user's reaction to the movie this matrix derives from. In the example shown above, the user specified a susceptibility of three when creating their account, and they are likely to react quite badly since other people with a similar susceptibility have reported ratings of three and four for this movie.