WordNet-Affect is an extension of WordNet that represents affective knowledge. It was developed by selecting and tagging a subset of synsets from WordNet that represent affective concepts. The resource is built upon WordNet Domains, a multilingual extension of WordNet, which includes domain labels for synsets. WordNet-Affect introduces an additional hierarchy of "affective domain labels" to annotate synsets representing affective concepts. The paper discusses the state of the art in affective lexicons, highlighting the limitations of lexical semantic approaches in capturing the full spectrum of emotional concepts. These approaches often rely on fixed semantic contexts and fail to distinguish different senses of the same word. To address this, WordNet-Affect integrates affective information from recent scientific research on emotion. WordNet-Affect was developed in two stages: first, identifying a core set of affective synsets, and then extending this core using relations defined in WordNet. A preliminary resource, AFFECT, was manually created containing 1,903 terms related to mental states. This resource was mapped to synsets in WordNet to identify the affective core. Affective information was then projected onto the corresponding senses of WordNet-Affect, with manual labeling used where necessary. WordNet-Affect contains 2,874 synsets and 4,787 words. It has applications in affective computing, including affective reasoning, information and tutoring tools, affective text sensing, and computational humor. The resource can enhance verbal expressivity, improve message empathy, and support the generation of humorous expansions. Future work includes extending the number of affective synsets, integrating WordNet-Affect with other linguistic resources, and emphasizing the importance of affective lexicon in communication and persuasion. The resource is freely available for research purposes.WordNet-Affect is an extension of WordNet that represents affective knowledge. It was developed by selecting and tagging a subset of synsets from WordNet that represent affective concepts. The resource is built upon WordNet Domains, a multilingual extension of WordNet, which includes domain labels for synsets. WordNet-Affect introduces an additional hierarchy of "affective domain labels" to annotate synsets representing affective concepts. The paper discusses the state of the art in affective lexicons, highlighting the limitations of lexical semantic approaches in capturing the full spectrum of emotional concepts. These approaches often rely on fixed semantic contexts and fail to distinguish different senses of the same word. To address this, WordNet-Affect integrates affective information from recent scientific research on emotion. WordNet-Affect was developed in two stages: first, identifying a core set of affective synsets, and then extending this core using relations defined in WordNet. A preliminary resource, AFFECT, was manually created containing 1,903 terms related to mental states. This resource was mapped to synsets in WordNet to identify the affective core. Affective information was then projected onto the corresponding senses of WordNet-Affect, with manual labeling used where necessary. WordNet-Affect contains 2,874 synsets and 4,787 words. It has applications in affective computing, including affective reasoning, information and tutoring tools, affective text sensing, and computational humor. The resource can enhance verbal expressivity, improve message empathy, and support the generation of humorous expansions. Future work includes extending the number of affective synsets, integrating WordNet-Affect with other linguistic resources, and emphasizing the importance of affective lexicon in communication and persuasion. The resource is freely available for research purposes.