Earworms from three angles Victoria Williamson & Daniel M端llensiefen A British Academy funded project run by the Music, Mind and Brain Group at Goldsmiths in collaboration with BBC 6Music
Points of contact for our studies
BBC 6Music site (Short reports, emails and texts)
What is left unansweredâ€Ś 1.
What triggers earworms in everyday life? Do they have a purpose?
Are some personalities more vulnerable than others?
What makes a tune sticky?
Project 1: Everyday triggers What triggers earworms?
Method: Qualitative analysis (grounded theory) of earworm episodes
Result: Identification of high-risk situations
Do they have a use?
Williamson et al., (2012) Psychology of Music
Earworm reports coded using grounded theory analysis techniques (2 independent raters)
6 Music corpus: 333 reports = 942 codes Survey (.com) corpus: 271 reports = 657 codes
Two models of codes show everyday earworm triggers and their relations
Emphasise importance of musical exposure but also memory function, and cognitive and affective state.
Some examples of memorable reports...
Stress - My ear worm is ‘Nathan Jones' by Bananarama. I first caught it in 1989 during my GCSE chemistry exam and have been plagued by it in moments of extreme stress since, e.g. wedding, childbirth etc” (6Music Text).
Person Association- My earworm today is ‘This Charming Man' by The Smiths because every time I see David Cameron, that song just appears in my head, for some particular reason” (6Music Emails)
1. Live Music (e.g. concerts or gigs) 1.Video Media (e.g. TV, film, internet site) 3. Radio 4. Private Music (e.g. in the home or the car) 5. Contagion (e.g. another individual singing or humming) 6. Learning (e.g. practising for performance or a lesson) 7. Public Music (e.g. restaurant, shop or gym) 8. Ringtones
Musical exposure – ubiquity (Sacks, 2007;
Beaman & Williams,
2010; Liikkanen, 2012)
But also non musical association triggers in (involuntary) memory
Heightened emotional states (including Media): Levels of encoding = ‘resurfacing’ potential?
Project 2: Individual differences Are some people more vulnerable than others?
Method: Statistical analysis of personality inventory (OCI-R) and factors of musical behaviour questionnaire (MuBQ) in relation to INMI factors (earwormery.com)
Müllensiefen et al. (in review)
Why are we interested in OC trait?
“people with obsessive compulsive disorder are more likely to report being troubled by earworms – in some cases medications for OCD can minimise the effects” (Levitin, 2006, p.151)
Let’s find out …
Individuals who measure highly on sub-clinical OC will experience more INMI that is more disturbing (Garcia-Soriano, Belloch, Morillo, & Clark, 2011)
People who are more â€˜musicalâ€™ will experience more frequent earworms (INMI) that are longer and more troubling (Beaman & Williams, 2011; Liikkanen, 2012)
1536 participants (58.1% women).
M Age = 34.2, SD = 12.6, range: 12-75
Exploratory analysis (n=512): â—Ś Factor analysis of musical behaviour and INMI questionnaire
Confirmatory analysis (n=1024): â—Ś Structural equation modelling to test hypotheses between OC, musical behaviour, and INMI.
Structural Equation Modelling: â—Ś Only some hypotheses confirmed â—Ś Good fit of final model: adjusted goodness-of-fit = 0.929 RMSEA index = 0.06
Results: Only Singing is linked (positively) to INMI But: Singing makes INMI more pleasant
OC traits = INMI Frequency and Disturbance Mediated evaluative response between OC & INMI Length: High OC => INMI disturbing => longer INMIs Similar paradoxical relationships found in OCD (Wegner et al., 1987)
To follow up
Should we be medicating earworms with OCD drugs?...
Should we prescribe singing to OCD patients? â€Ś
Posters on individual differences
G. A. Floridou, V. J. Williamson, D. Müllensiefen “Contracting Earworms: The Roles of Personality and Musicality” (Friday 3.30pm)
M. Wammes, D. Müllensiefen,V.J. Williamson: “Schizotypal Influences on Musical Imagery Experience” (Wednesday 11am)
Project 3: Stickiness of tunes What is it that makes a tune sticky?
Method: Computational analysis of tunes from frequently reported earworms
Tools: FANTASTIC software package i.abs.std =
Result: Classification model predicting stickiness
∑ (∆p i
) = 2.83
Step 1: Gathering earworms •
~2000 participants (.com survey)
1960 different earworm tunes (Artist, song title, exact part)
Top earworm list: 5.5% of songs identifiable and named at least 3 times
Control for popularity and recency and find ‘sticky tunes’: => tunes with a positive residual after poisson regression (using popularity data as predictors)
Find tunes most similar to INMI tunes (match by genre and chart success etc.) Use melodic features (Müllensiefen, 2009) of tunes to predict INMI vs non-INMI tunes (logistic regression)
Data Most frequent earworm tunes: artist lady gaga lady gaga journey katy perry queen
song bad romance alejandro don't stop believing california gurls bohemian rhapsody
incs 13 11
hi.entry 1 7
weeks 38 10
entry.date 281 253
exit.date 15 183
genre pop pop
Similarly successful but never mentioned as earworms: artist gorillaz jessica simpson stereophonics nelly elvis presley
song feel good inc. these boots are made for walkin' handbags and gladrags my place way down
0 0 0
4 1 1
15 11 13
3164 2164 12054
3059 2087 11963
rock pop rock
Earworm classification model p (earworm = 1) =
1 1+ e
−(1.079+ 0.064 ⋅ d.median -0.723 ⋅ i.leaps)
= Longer durations and smaller intervals make tunes sticky (maybe because they are easier to sing?) BUT results only preliminary, because: • • • •
Melody only one aspect of INMI Small sample (58 songs) Interactions of features Different types of earworms => different structural models?
Latest analysis on 214 tunes: Sebastian Finkel (Friday 3.30pm poster session)
Musical exposure important (Sacks, 2007; Bailes, 2012) that is recent and repeated (Beaman & Williams, 2010); but so is the activity of nonmusical, involuntary memories
State of mental arousal (wakefulness, excitement and stress) and ‘mind wandering’ – a possible function? (Leverhulme Grant)
Singing behaviour predicts features of INMI plus ease of singing may predict stickiness: activity of brain areas?
Melodic structure alone is a powerful predictor of inherent stickiness
Multi-method approach for generating future hypotheses
Special thanks to Sagar Jilka, Sebastian Finkel, Josh Fry, Alex Handler, Mandi Goldberg, Andre Lira & all at the BBC
THANK YOU YOU!! MUSICPSYCHOLOGY.CO.UK (LIVE--ISH BLOG OF ICMPC/ESCOM) (LIVE
QUESTIONS?? This project was kindly supported by: