Affective computing is an emerging research area focused on the development of systems with the ability to recognize, process and simulate human emotions in order to improve a user’s experience in an interactive system. One of the possible fields of application of affective computing is marketing and advertising, where the application of emotion analysis techniques on the opinions made by users in different contexts has been evidenced, being a challenge the analysis of different types of multimedia content, such as advertising jingles. Thus, in this article we propose as a contribution the development of an emotion analysis study on the advertising jingles of the main candidates for mayor of Cartagena-Colombia in the period 2020-2023. For the development of this study, the acoustic properties of arousal and valence present throughout the audio track of each advertising jingle were taken into consideration, in such a way that through these properties it is possible to classify an audio fragment into an emotion belonging to the circumflex model or Russell model. To perform the segmentation of the audio track and the extraction of the acoustic properties of arousal and valence, we developed the MUSEMAN tool, which allows determining the emotions fluctuation in the advertising jingle audio track.