The aim of judgment aggregation is to make collective decisions based on the judgments of individual agents. Some rationality conditions governing the expected behavior of the aggregation function must be considered. However, impossibility theorems show that designing an aggregation function satisfying all desirable properties is not feasible. While some rationality conditions are very nat-ural ones, other ones are more disputable. We show that this is the case of the systematicity condition that prevents from electing issues with more votes than others. We rather promote a neutral-ity and a swap optimality condition. Swap optimality ensures that among two possible results, the one with the best support (number of votes) is chosen. We propose a new family of judgment aggrega-tion methods based on the support (number of votes) that receives each issue.