We describe a new method for sentiment load annotation of the synsets of a wordnet, along the principles of Osgoods Semantic Differential theory and extending the Kamp and Marx calculus, by taking into account not only the WordNet structure but also the SUMO/MILO (Niles & Pease, 2001) and DOMAINS (Bentivogli et al., 2004) knowledge sources. We discuss the method to annotate all the synsets in PWN2.0, irrespective of their part of speech. As the number of possible factors (semantic oppositions, along which the synsets are ranked) is very large, we developed also an application allowing the text analyst to select the most discriminating factors for the type of text to be analyzed. Once the factors have been selected, the underlying wordnet is marked-up on the fly and it can be used for the intended textual analysis. We anticipate that these annotations can be imported in other language wordnets, provided they are aligned to PWN2.0. The method for the synsets annotation generalizes the usual subjectivity mark-up (positive, negative and objective) according to a user-based multi-criteria differential semantics model.