This degree thesis presents an examination of a collection of semantic associations evoked by Italian verbs. Data were collected by asking Italian native speakers to provide associations to a list of 312 verbs in a web experiment. In the current investigation, it is assumed that associations reflect salient linguistic and conceptual aspects of verb meaning. Given this assumption, the first step was to identify the types of information provided by speakers by distinguishing and quantifying the relationships between stimulus and response. The verb associations were investigated on three linguistic dimension: (a) the responses were distinguished with respect to the part-of-speech tags; (b) for each verb associate, the semantic relation between the target and the response was identified; (c) the conceptual roles of the noun responses with respect to the target verb were determined. As a further investigation, a Self-Organizing-Map was used in order to perform a clustering to the verbs, as based on the associations. The general clustering properties are discussed in order to discover which properties are most relevant in the representation of different verbs.