(originally posted here)

I was going to reply to Paul’s comment and this actually became a post.  Having suggested the idea of inversed tag clouds as a means to enhance serendipity, Paul pointed out two cases in which serendipity can be desirable: 1) where you know that all the entries are of a certain standard and 2) where the most popular ones are likely for that reason to be less interesting.

In this respect, I would like to speculate to what extent serendipity can be desirable in large-scale deliberation processes, and how this serendipity can be induced online. To give it a fancy name, “induced redistributive serendipity”.

To make my point simpler, let’s think for instance of a cloud based on the number of views that an article / argument receives. In this case, the most viewed articles / arguments (or their respective tags) become more visible as more people view them, generating a snowball effect of intuitive mimesis.

This is more or less what happens in flawed models such as the ranking system of phase 1 of the “Open Government Initiative”, where interventions at the initial stage can (and often do) produce huge variations in the outcome. In this case, for instance, the idea of an inversed cloud could neutralize these undesirable effects.

Now, consider an online deliberation where, at least in theory, all the arguments are important and should be objects of consideration. Here, a traditional tag cloud could have disastrous consequences for the quality of deliberation. Once more, an inversed cloud based on the number of times an argument is viewed (the least viewed become more visible) could be useful for the purpose of online deliberation.

This could be particularly applicable for large-scale online deliberation. Given that people rarely take the time to go over most of the arguments that are available, an inversed cloud could have a redistributive function. As the most read arguments become less visible and vice-versa, one would expect a better distribution of the number of views each argument receives. Finally, for the participants, this could lead them to come across information that they were not looking for in the first place.

In other words, my question is: could this “induced redistributive serendipity” be used in large-scale online deliberation?