This pattern is much like the Vote To Promote pattern. It differs from the Vote To Promote pattern by having different end means. The end means is to allow users to guide other users about what is good and bad rather than to promote what is interesting.
The pattern consists of a number of mechanisms that work together:
The Rate Content pattern promotes community participation and can assist you in parting out good quality content from bad quality content. This is especially useful when your website relies on user submitted content.
Rating content is about handling risk from the user’s point of view. Will a user on eBay cheat me or is a book on amazon worthwhile my time and money?
The main reason to use the Rate Content pattern is assist the user in managing risk. Examples of such risk are spending money on buying a product or from investing time on another user.
When implementing a rating system, you need to consider a number of things in relation to what it should be used for and how it should be communicated:
Who is doing the rating
When reading reviews about an item and seeing how other users rate a given item a number of concerns are bound to be risen by the user: “Is the rating and review honest and authentic?”, “Are the users who rated a given item like me?”, and “Do the reviewers posses the relevant competence to review the good or service in question?”.
Amazon and Netflix has solved this problem by letting people rate the ratings: was this review helpful for you?
What is being rated
Be clear when communicating what is being rated and make sure that the user knows exactly what he or she is rating. If what is being rated seems ambiguous, the value of the review for other users in turn diminishes. For instance, if website collects good computer deals that can be rated by the website’s users, is it the trustworthyness of the deal’s seller, the products, or the price that is being rated?
Consider making your rating system multi-dimensional, or simply be clear about what – exactly what – is being rated.
What behavious are we trying to encourage or discourage?
Like with the similar community driven patterns, several pitfalls can make or break the success of the Rate Content pattern. Are some users trying to promote or demote certain items? – perhaps their own or their competitors product – maybe their friends or foes. You might want to setup a number of measures to prevent users from misusing the system, such as limiting the maximum activity of a user, looking out for malicious activity, or promote trusted key users to count more than others
Design your rating system so that you encourage the behavior you want. Making your rating system multi-dimensional by breaking up the full rating into sub-parts that by their title explain exactly what you want measured (rated), is one way of solving this problem.
On amazon, each rating is accompanied by a textual review explaining the rating given. The specific rating is given on a scale of 1-5 and is beside the textual review also presented together with the name of the author and his location.
At Amazon, you can take a closer look into the average rating (in this case 4.5 stars) to for instance see if the scores given were all high, all low, or in between. Furthermore, the two most helpful reviews in respectively the high and low and of the scale help point out the most relevant critique or praise of the given product.
At UI-patterns, users can let the rest of the world know, if they think a pattern represents a good practice or not.
The quality and helpfulness of each blog post at Ajaxian.com can be rated. But what is really being rated? The importance of the story, the quality of the story, the helpfulness of the story? The ratings given are ambiguous.