One of the widely used approaches to Sentiment Analysis (SA) is lexicon-based approach that depends on sentiment-annotated lexical resources (such as SentiWordNet (SWN)). A broad variety of such resources are Synsetbased Lexical Databases (SLDs) (e.g. SWN is based on WordNet (WN)) and represent sentiment degrees of synonym groups of LDs, called "synsets." However, synsets themselves were open to criticism because although, in reality, not all the members of a synset represent its meaning with the same degree, in SLDs, they are, identically, considered as members of their synset. Therefore, the fuzzy version of synsets was proposed in a small number of previous studies. Fuzzy synsets can upgrade such lexicon-based SA by which the future SA systems can discriminate between word-senses of a same synset, how much each of them contains the sentiment load of that synset. But, to the best of our knowledge, none of the studies on fuzzy synsets has proposed any algorithm for providing fuzzy versions of "predefined synsets" of an SLD. In this study, we present the idea of an algorithm for constructing fuzzy version of any SLD of any language, given a corpus of that language and a word-sense-disambiguation system of that language/SLD.