Earworms from Three Angles

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Earworms from Three Angles EarwormsEarworms fromfrom threethree anglesangles 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 Points of contact for our studies Earwormery.com 6Music site (Short reports) WhatWhat isis leftleft unansweredunanswered …… 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? ProjectProject 1:1: EverydayEveryday triggerstriggers 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? ResultsResults (Williamson(Williamson etet al.,al., 2012)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. SomeSome examplesexamples ofof memorablememorable reports...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) 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 Emails) MusicalMusical mediamedia 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 DiscussionDiscussion 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? ProjectProject 2:2: IndividualIndividual differencesdifferences 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 MMüüllensiefenllensiefen etet al.al. (( inin reviewreview )) 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 … HypothesesHypotheses 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 sub- clinical OC will experience more INMI that is more disturbing (Garcia-Soriano, Belloch, Morillo, & Clark, 2011) MethodMethod 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. ModellingModelling 1)1) FactorFactor structuresstructures INMI: ◦ Factor INMI Disturbance ◦ Individual variables: INMI Frequency, INMI Length, INMI Unpleasantness Musical Behaviour Factors: ◦ Musical Practice ◦ Musical Professionalism ◦ Listening Engagement ◦ Singing ModellingModelling 2)2) TestingTesting HypothesesHypotheses Structural Equation Modelling: ◦ Factor structure confirmed ◦ Only some hypotheses confirmed ◦ Good fit of final model: χ2(85) = 397.79, p < .0001 adjusted goodness-of-fit = 0.929 RMSEA index = 0.06 ResultsResults 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? … 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 ProjectProject 3:3: StickinessStickiness ofof tunestunes What is it that makes a tune sticky? Method: Computational analysis of tunes from frequently reported earworms Tools: FANTASTIC software 2 package ∑ (∆pi − ∆p) i.abs .std = i = 2.83 N −1 Result: Formula predicting 1 stickiness p (chart_entry =1) = 1+ e−(772.4 + 141.2 ⋅ pitch_range - 4731.3 ⋅pitch_entropy) Masters Project: Sebastian Finkel (Friday 3.30pm poster session) StepStep 1:1: GatheringGathering earwormsearworms • ~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 MethodMethod 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) DataData Most frequent earworm tunes : Similarly successful but never mentioned as earworms : EarwormEarworm classificationclassification modelmodel 1 p (earworm =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 • No combinations / interactions of features • Different types of earworms => different structural models? FINALFINAL conclusionsconclusions 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... icmpc12earworms.comicmpc12earworms.com THANKTHANK YOUYOU IF INTERESTED: MUSICPSYCHOLOGY.CO.UK QUESTIONS??QUESTIONS?? This project was supported by: WhyWhy dodo wewe care?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? MuBQMuBQ scalescale (Now(Now ‘‘GoldGold MSIMSI ’’)) The MuBQ comprises 16 items relating to musical behaviour and experience Amount of attentive and background listening, the number of conc erts 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 tra ining, 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. INMIINMI scalescale 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).
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