Article rankings are a tool widely used among online newspapers and social networks. Sometimes they come as little widgets in the margin while at other times, rankings are the website’s main feature. There are many ways to rank articles, but what is good for your website and how effective are these ranking systems?

Most Read

The most common ranking system has a minor weakness. What is read most by readers might not be the best article. It maybe has an interesting picture or the headline is thrilling, but when you click on it and read on, the article is in fact rather weak. By this time, it has been already counted for the ranking. So articles, which are not interesting for most people, climb up the ranking and readers who use the “Most Read” tool are disappointed.

Most Recommended

A ranking can be trusted more when readers actively recommend articles. The whole concept of Digg depends on this. Users ‘digg’ (recommend) articles, the best articles will then climb up the charts that are browsed by other users. This system has proven effective and Digg has been extremely successful with it.

Most Recommended by Authors

Online newspapers will not let their readers alone decide which stories to put on top. The main skill of a newspaper is to know what is important right now, and many readers trust a professional more than the opinion of the masses.

Today, every news homepage is a ranking of what is recommended by the authors. A “Most Recommended by Authors” widget might still be a good function if you want to keep articles on top beyond the actuality of the homepage or if you don’t have a very up-to-date website.

Most Recommended by Peer-Group

With the New York Times application, “Times People”, users can follow other users and see what they recommend. If you have a very large group of people you follow because you share the same interests with them, a “Most Recommended” function within this group would potentially produce the most relevant results for you – better results than any journalist or system could ever provide.

Most Blogged

A “Most Blogged” ranking is very similar to a “Most Commented” one. Articles that have been linked on a blog are probably even more relevant.

Most Searched

“Most Searched” displays the articles that users are looking for through the website’s search function or through a Google search. It can dig up articles from the archives – if a certain topic written about some time ago again becomes relevant to users because of certain events for example.

Most E-Mailed

This feature is almost the same as “Most Recommended”. People usually email articles to recommend them to somebody else.

Most Commented

This feature is perfect for those who like to communicate with other users, as it shows where peoples discuss the most. However, users who do not like to comment might also like this ranking, as it supports topics that polarise and might be interesting to read because of this.

Most Saved

“Most Saved” might be a good ranking too. Users generally only save articles that have some kind of value to them. It is similar to bookmarking services like delicious.

All of these functions can be filtered by category, making them more useful for those interested in a specific topic. A “Most Popular” teaser within a certain news department should show the best articles for that department only.

Depending on the article release frequency, “Most Popular” teasers should display the best articles within a certain period of time – within the past 24 hours or past week for instance. After a while, all-time favourites will not change anymore since these articles are being viewed or commented on even more because of the teasers.

A good way is to show recent articles as default and wider periods of time with tabs so that users will get the best stories of the week or the month if they missed something.