Earworms from three angles

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1 Earworms from three angles Dr. Victoria Williamson & Dr 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 6Music site (Short reports)

3 What is left unanswered 1. What triggers earworms? Do they have a purpose? 2. Are some people/personalities more vulnerable than others? 3. What is it that makes a tune sticky?

4 Project 1: Everyday triggers What triggers earworms? Method: Qualitative analysis (grounded theory) of earworm episodes Tools: Surveys and interviews Result: Identification of high- risk situations Do they have a use?

5 Results (Williamson et al., 2012) 6 Music corpus: 333 reports = 942 codes Survey (.com) corpus: 271 reports = 657 codes Two models created showing 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 s) Word Association - Michael Jackson PYT (Pretty Young Thing). On my journey, I read a number plate on a car that ended in the letters "EYC" which is NOTHING LIKE "PYT" but for some unknown reason, there it was - the song was in my head (Survey data). Recent - My bloody earworm is that bloody George Harrison song you played yesterday. Woke at 4.30 this morning with it going round me head. PLEASE DON'T EVER PLAY IT AGAIN!! (6Music s)

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, non musical triggers in memory Mental time travel (Tulving, 2002), that is involuntary (IAM; Bernsten, 2009) Heightened emotional states : Levels of encoding = resurfacing potential? Congruence? States of Mind?

10 Project 2: Individual differences Are some people more vulnerable than others? Method: Statistical analysis of personality inventory and musical behaviour questionnaire Tools: Questionnaire on thinking patterns (OCI-R), musical behaviours (MuBQ) and INMI (earwormery.com) Question: Link between personality types, musical behaviours and earworm (INMI) experiences

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 mediations for OCD can minimise the effects (Levitin: p.151) Let s find out

12 Hypotheses People who are more musical will experience more frequent earworms (INMI) that is longer and more troubling (Beaman & Williams, 2011 Liikkanen, 2012) Individuals who measure highly on subclinical OC will experience more INMI that is more disturbing (Garcia-Soriano, Belloch, Morillo, & Clark, 2011)

13 Method 1536 participants (58.1% women). M Age = 34.2, SD = 12.6, range: 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 Modelling 1) Factor structures INMI: Factor INMI Disturbance Individual variables: INMI Frequency, INMI Length, INMI Unpleasantness Musical Behaviour Factors: Musical Practice Musical Professionalism Listening Engagement Singing

15 Modelling 2) Testing Hypotheses Structural Equation Modelling: Factor structure confirmed Only some hypotheses confirmed Good fit of final model: χ2(85) = , p <.0001 adjusted goodness-of-fit = RMSEA index = 0.06


17 Results Only Singing as musical behaviour is linked (positively) to INMI But: Singing makes INMI more pleasant OC traits are linked to INMI Frequency and INMI Disturbance Mediated evaluative response between OC and INMI Length: High OC trait => INMI more disturbing => longer INMIs paradoxical relationship found in clinical OCD: high efforts to suppress intrusive thoughts make these thoughts longer ( rebound effect ) and more frequent ( immediate enhancement effect ) (Wegner et al., 1987) Should we be medicating earworms with OCD drugs?... Should we prescribe Singing to OCD patients?

18 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

19 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 = i ( p i p) 2 = 2.83 N 1 Result: Formula predicting stickiness p (chart_entry =1) = Masters Project: Sebastian Finkel (Friday 3.30pm poster session) 1 1+ e ( pitch_range pitch_entropy)

20 Step 1: Gathering earworms ~2000 participants (.com survey) Recent earworm and a Frequent earworm Artist, song title, exact part 1960 different earworm tunes Top earworm list: 107 songs (5.5%) identifiable and named at least 3 times

21 Method 1. Control for popularity and recency and find sticky tunes : => 29 tunes with a positive residual after poisson regression (using popularity data as predictors) 2. Find 29 tunes most similar to 29 INMI tunes (match by genre, artist and chart success etc.) 3. Use melodic features (Müllensiefen, 2009) of tunes to predict INMI vs non-inmi tunes (logistic regression)

22 Data Most frequent earworm tunes: Similarly successful but never mentioned as earworms:

23 Earworm classification model p (earworm =1) = 1 ( d.median 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 No combinations / interactions of features Different types of earworms => different structural models?

24 FINAL conclusions Musical exposure important (Sacks, 2007) that is recent and repeated (Beaman and 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) Individual differences in singing only predicts some features of INMI plus ease of singing may predict stickiness: activity of brain areas? Earworms may have structural melodic triggers why do our minds react to patterns in this way? Wider implications for other spontaneous cognitions (including creativity and rumination), memory processes, music perception and encoding, personality research...

25 icmpc12earworms.com



28 Why do we care? Spontaneous Involuntary Cognition mind popping (Christoff et al. 2004; Klinger & Cox, 1987) Up to 40% of thoughts (McVay et al. 2009) One of many; but accessible, classifiable & regular Window into our unconscious, memory processes, mental control abilities... Ok we are interested! So what do we know?

29 MuBQ scale (Now Gold MSI ) The MuBQ comprises 16 items relating to musical behaviour and experience Amount of attentive and background listening, the number of concerts attended, self-assessed singing ability, frequency of sing-along behaviour, importance of music in the participant s life, self-defined levels of musical competence, the type and extent of musical training other skilled musical activities, and the possession of absolute pitch. Maximum-likelihood principal factor analyses Final four-factor solution = 52.6%: Musical Practice, Music Professionalism, Listening Engagement and Singing.

30 INMI scale The INMI-Q comprises 7 items The length and frequency of INMI episodes, their subjective unpleasantness, and the frequency with which an individual tries to get actively rid of his/her INMI, the effort necessary for controlling them, their interference with other tasks, and the degree to which an individual feels their INMI experiences are worrisome Maximum-likelihood principal factor analyses Final four-factor solution = 48%: INMI Frequency, Length, Unpleasantness, Disturbance (intrusion and concern)