1. Earworms from three angles
Victoria Williamson & Daniel Müllensiefen
A British Academy funded project run by the Music, Mind and
Brain Group at Goldsmiths in collaboration with BBC 6Music

2. Points of contact for our studies
Earwormery.com
BBC 6Music site (Short
reports, emails and texts)

3. What is left unanswered…
1. What triggers earworms in everyday life?
Do they have a purpose?
2. Are some personalities more vulnerable than
others?
3. What makes a tune sticky?

4. 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?

5. 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.

7. 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)

8. Musical media
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

9. Discussion
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?

10. 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)

11. 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 …

12. Hypotheses
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 ‘musical’ will experience
more frequent earworms (INMI) that are
longer and more troubling (Beaman & Williams, 2011;
Liikkanen, 2012)

13. Method
1536 participants (58.1% women).
M Age = 34.2, SD = 12.6, range: 12-75
Exploratory analysis (n=512):
◦ Factor analysis of musical behaviour and INMI
questionnaire
Confirmatory analysis (n=1024):
◦ Structural equation modelling to test hypotheses
between OC, musical behaviour, and INMI.

14. Testing Hypotheses
Structural Equation Modelling:
◦ Only some hypotheses confirmed
◦ Good fit of final model:
adjusted goodness-of-fit = 0.929
RMSEA index = 0.06

15. 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)

16. To follow up
Should we be medicating earworms with OCD drugs?...
Should we prescribe singing to OCD patients? …

17. 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)

18. 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
2
∑ (∆p
i i − ∆p ) = 2.83
i.abs.std =
N −1
Result: Classification
model predicting
stickiness

19. 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

20. Method
1. Control for popularity and recency and
find ‘sticky tunes’:
=> tunes with a positive residual after poisson
regression (using popularity data as predictors)
2. Find tunes most similar to INMI tunes (match
by genre and chart success etc.)
3. Use melodic features (Müllensiefen, 2009) of tunes
to predict INMI vs non-INMI tunes (logistic
regression)

21. Data
Most frequent earworm tunes:
artist song incs hi.entry weeks entry.date exit.date genre
lady gaga bad romance 13 1 38 281 15 pop
lady gaga alejandro 11 7 10 253 183 pop
don't stop
journey believing 11 6 47 477 149 rock
katy perry california gurls 10 1 6 43 1 pop
bohemian
queen rhapsody 7 1 17 12699 12580 rock
Similarly successful but never mentioned as earworms:
artist song incs hi.entry weeks entry.date exit.date genre
gorillaz feel good inc. 0 2 39 1940 1667 pop
these boots are
jessica simpson made for walkin' 0 4 10 1800 1730 pop
handbags and
stereophonics gladrags 0 4 15 3164 3059 rock
nelly my place 0 1 11 2164 2087 pop
elvis presley way down 0 1 13 12054 11963 rock

22. Earworm classification model
1
p (earworm = 1) = −(1.079+ 0.064 ⋅ d.median -0.723 ⋅ i.leaps)
1+ e
= 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)

23. FINAL conclusions
Musical exposure important (Sacks, 2007; Bailes, 2012) that is recent
and repeated (Beaman & Williams, 2010); but so is the activity of non-
musical, 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

24. icmpc12earworms.com
Special thanks to Sagar Jilka, Sebastian Finkel, Josh Fry,
Alex Handler, Mandi Goldberg, Andre Lira & all at the BBC

25. THANK YOU!
YOU!
MUSICPSYCHOLOGY.CO.UK
(LIVE-
(LIVE-ISH BLOG OF ICMPC/ESCOM)
QUESTIONS??
This project was kindly supported by: