8–12 Sept 2026
Europe/Vienna timezone

Chills and Betting Bills - Audio Features, Listener Emotions and the Success of ESC Songs

FA2026/410
9 Sept 2026, 15:00
3h
Messehalle (Poster+Exhibition) (Messe Congress Graz)

Messehalle (Poster+Exhibition)

Messe Congress Graz

Speaker

Helene Lindenbauer (Universität Wien)

Description

Each year, the Eurovision Song Contest (ESC) generates speculation about the winning song. Previous research about Eurovision Song Contest Songs has mainly examined the musical features of past ESC participants, while the listeners emotions and chill experiences have not yet been combined with it. This study investigated whether acoustic and emotional differences can be measured between highest- and lowest-rated ESC songs based on pre-final betting odds (April 2026), aiming to capture potential predictors of final outcomes. Twenty-seven participants (17f, 10m; 19-57 years old, mean 28) listened to three lowest- and three highest-rated songs, while skin conductance was measured via Mindfield eSense sensors and valence, arousal (Circumplex Model) and experienced chills were reported. After each song, participants were asked to rate the song liking (“not” to “very much”) and how often they have heard it before (“not once” to “many times”). Further, they filled out a personality questionnaire (SEPPO) as research indicates preference and physiological reaction differences. Audio features were extracted using a.o. MIRToolbox and PADMEA.There were significantly more experienced chills for the three higher-rated songs (t(3,first_vs._3,last)=3.264, p<0.05). Differences (t-Tests) between personality traits, song liking, valence, arousal, and musical audio features between the three lowest- and three highest-rated songs were noticed. Based on the acoustic audio feature analysis the valence also depends on the songs Roughness (Vassilakis, t(3,first_vs._3,last)= -7.528, p<0.01) and Brightness (t(3,first_vs._3,last)= 11.935, p<0.01). Further results will be interactively presented (https://muwiserver.univie.ac.at/esc2026/) at the conference.

Authors

Helene Lindenbauer (Universität Wien) Christoph Reuter (Universität Wien) Sarah Ambros (Universität Wien)

Presentation materials