Why Reddit and other content-aggregation sites need to weigh clusters of users and your relationship to them in their ranking scores

On the internet, web surfers, in the search of information, always strive for recommendations. The solutions for generating recommendations become more difficult because of exponential increase in information domain day by day. In this paper, we have calculated entropy based similarity between users to achieve solution for scalability problem. Using this concept, we have implemented an online user based collaborative web recommender system. In this model based collaborative system, the user session is divided into two levels. Entropy is calculated at both the levels. It is shown that from the set of valuable recommenders obtained at level I; only those recommenders having lower entropy at level II than entropy at level I, served as trustworthy recommenders. Finally, top N recommendations are generated from such trustworthy recommenders for an online user. http://arxiv.org/abs/1201.4210

Basically, if you disagree with someone more than a certain threshold, none of their recommendations seem to matter to you. Surprise surprise.