Visualizing the Knowledge Space of Music · 2017-07-04 · Goal: Map the knowledge space of music I...

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Visualizing the Knowledge Space of Music IAML 2017, the 66th IAML Congress Glenn Henshaw, Fan Yun June 22, 2017

Transcript of Visualizing the Knowledge Space of Music · 2017-07-04 · Goal: Map the knowledge space of music I...

Page 1: Visualizing the Knowledge Space of Music · 2017-07-04 · Goal: Map the knowledge space of music I Co-Word Analysis attempts to map the knowledge space of a given eld by measuring

Visualizing the Knowledge Space of MusicIAML 2017, the 66th IAML Congress

Glenn Henshaw, Fan Yun

June 22, 2017

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What is music scholarship?

I Music scholarship is hard to defineI Deeply interdiciplinary.I It’s a young field.

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What is music scholarship?

Examples:

I Musicology: Richard Wagners opposition to animalexperimentation: A visionary social critic

I Ethnomusicology: A bird tradition in the west of the BalkanPeninsula

I Music pedagogy: From Mississippi hot dog to Arizonacactus

I Music therapy The use of music with chronic food refusal: Acase study

I Popular music studies Crossing cinematic and sonic barlines: T-Pains Cant believe it

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Goal: Map the knowledge space of music

I How can the music be divided into subfields?

I What are the principle subfields?

I What are the emerging subfields?I How do these subfields connect/interact?

I InternallyI externally

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Goal: Map the knowledge space of a given field

I Inskip and Wiering Conducted surveys of Musicologicalscholarship.

I Leech-Wilkinson considered community behavior from ahistorical perspective.

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Goal: Map the knowledge space of a given field

I Expert surveys tend to be costly and slow endeavors.

I Expert bias.

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Goal: Map the knowledge space of music

I Co-Word Analysis attempts to map the knowledge space ofa given field by measuring and analyzing the strength of theassociations between terms (keywords, indexed terms, orwords from a corpus)

I The strength of the association between terms is based onhow frequently they co-appear in documents.

I We use the results of co-word analysis to hierarchically clusterthe terms.

I We visualize the clusters with dendrograms, weightedgraphs, and strategic diagrams.

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Visualization techniques

I Dendrograms: detailed information on the relationshipbetween terms and clustering.

I Weighted graphs: details of each cluster

I Strategic Diagram: Local and global view of the clusters

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What is RILM?

I A comprehensive music bibliography featuringI abstracts and citationsI 143 languagesI 1967 – presentI 875,000 records

I RILM indexing represents hierarchical relationships withbroader and narrower topics.

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The Data

I Almost all academic music articles (2000-2015)

I 263,656 Rows

I 59,908 Articles

I 25,297 distinct terms (lvl1)

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15 Most common terms

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Co-occurrence

DefinitionFor two terms, i and j , their co-occurrence is defined as

Ci ,j = How often i and j appear in the same article

Example

The terms ’aesthetics’ and ’popular music’ apear together in 123articles.

C’aesthetics’,’popular music’ = 123

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From matrix to graph using the matrix CI Dots (nodes) are terms.I Lines between terms indicate that C > 4.I Colors indicate terms that are highly interconnected (clusters).

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From matrix to graph using the matrix CI Despite its beauty, we could not obtain valuable information

from this graph!

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From matrix to graph using the matrix C

I High frequency terms dominate the connections.

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Cosine similarity

Cosine similarity (CS) is defined as

CS(i , j) =

√C 2ij

CiiCjj.

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Example

Let

i = ’China’ j = ’popular music’k = ’mathematics’ l = ’scales’.

Then,

Cij = 151 CS(i , j) =√

1512/(5084 · 2388) = .04

Ckl = 15 CS(k , l) =√

152/(309 · 303) = .05.

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Hierarchical Clustering (a rough sketch)

I Distance between individual terms: d(i , j) = 1− CS(i , j).

I At the start, each term, ti , is contained in its own clusterci = {ti}.

I Define distance between clusters D(ci , cj).I Many ways to do this

Repeat until there is only one cluster:

I Find two clusters of minimal distance, i.e. minD(ci , cj).

I Merge the clusters ci and cj into a cluster ci&j .

I Delete the clusters ci and cj .

We visualize Hierarchical clustering with a dendrogram.

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Hierarchical Clustering (a rough sketch)

A

BC

D

E

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Hierarchical Clustering (a rough sketch)

A

BC

D

E

A B

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Hierarchical Clustering (a rough sketch)

A

BC

D

E

A B E C

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Hierarchical Clustering (a rough sketch)

A

BC

D

E

A B E C

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Hierarchical Clustering (a rough sketch)

A

BC

D

E

A B E C D

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Dendrogram (49 Clusters)

0.00.51.01.52.02.53.03.5conservation and restorationreligious institutionsinstruments--keyboard (organ family)instrument builders--organsound recordingsperformers--popular musicperforming groups--popular musiceconomicssound recording and reproductionmass mediaadvertising and marketingsociologyrockpopular musiccultural studiesUnited States of Americablack studiessong textship hopsexuality and genderwomen's studiesmanuscriptsnotation and paleographychant--Christian (Western)source studieseditingSchubert FranzSchumann RobertBrahms Johannesinstruments--keyboard (piano family)accompanimentinterpretationChopin FrédéricarrangementsLiszt FranzBeethoven Ludwig vanMozart Wolfgang AmadeusHaydn Josephperformance practicetempoBach Johann Sebastianinstruments--keyboardcompositionelectronic music and computer musicsonoritymixed mediatimeDebussy Claudescienceaestheticsphilosophyanalysiscomputer applicationscounterpointcreative processStravinsky IgorSchoenberg Arnoldserialismmathematicstheoriststheoryintervalsmodalityscalespoetrytext settingrhythm and metermelodyharmonytonalitytextureformmotive and themeperceptionpitchsingingacousticsanatomy and physiologyvoicetherapychildrenpedagogycareersaudiencesAustraliaamateursmovement and gestureconductingaptitude and abilitypsychologyperformancemedicine--by topicinstrumental playingpracticing and rehearsingensemble playingfilm and videofilm music and television musicdirectors producers etc.performing organizationsperformers--conductingoperaVerdi GiuseppeWagner Richarddramaturgychoreographers

ajkovskij Pëtr Il'imusical theater--popularpremieresliteraturelibretto--by librettistimprovisationperformers--jazz and bluesjazzanecdotes reminiscences etc.academic institutionspedagoguesperformers--pianoobituariesmusicologistsperformers--voiceperformers--traditional and neotraditional musicperformers--organsocieties associations fraternities etc.--nat.CanadaGermanycultural policiespoliticswars and catastrophesreceptionFrancecriticismperiodicalslibraries museums collectionscorrespondencesong--popular and traditionalLithuaniaethnomusicologyethnomusicologistsHungaryBartók Bélasong--by composerdiscographiescatalogues and indexes--by nameinstrumental musicvocal musicgenre studiessemioticstwenty or twenty-first-century musicsemanticssong--generalUnited Kingdom--Englandreligion and religious music--Christianity (Protestant)nationalismCzech RepublicBrazilidentity--collectiveSpaininstruments--string (guitar family)AustriaItalyreligion and religious music--Christianity (Roman Catholic)religion and religious music--Christianitypolyphonychoral musicperforming groups--small ensemblesinstruments--string (violin family)performers--violinperformance venuesRussian Federationfestivalscompetitions awards and prizesmusicologycongresses conferences symposiaChinadramatic artsinstruments--mechanicalinstruments--collectionsGreecetemperament and tuningantiquityinstruments--percussion (bells)dancedance musicIndiainstruments--percussion (drum)ceremoniesinstruments--wind (free reed family)terminologylanguageWestern musichistoriographyKoreaEuropeAsiainstruments--string (zither family)instruments--string (lute family)Japantimbreinstrumentation and orchestrationinstruments--wind (woodwind flute family)instruments--wind (brass)instruments--wind (woodwind reed family)iconographyinstrumentsvisual and plastic artssymbolismnature

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Density and Centrality

For each cluster we calculate:

I Density - Average strength of all the connections within acluster

I Centrality - The square root of the sum of the squares of allconnections to outside clusters

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Strategic Diagram

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Strategic Diagram

Centrality

Density

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Strategic Diagram

Centrality

Density

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Cluster: Form

motive and theme

texture

harmony

form

rhythm and meter

tonality

melody

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Strategic Diagram

Centrality

Density

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Cluster: Popular Recordings

performers--popular music

performing groups--popular music

sound recordings

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Strategic Diagram

Centrality

Density

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Cluster: Pedagogues

anecdotes reminiscences etc.

performers--piano

pedagogues

academic institutions

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Strategic Diagram

Centrality

Density

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Cluster: Rock

sociology

rock

cultural studies

popular music

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Strategic Diagram

Centrality

Density

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Cluster: Mechanical instruments

instruments--collections

instruments--mechanical

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Strategic Diagram

Centrality

Density

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Cluster: Classical

Haydn Joseph

Mozart Wolfgang Amadeus

Beethoven Ludwig van

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Strategic Diagram

Centrality

Density

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Cluster: Organ

instruments--keyboard (organ family)

instrument builders--organ

religious institutions

conservation and restoration

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Strategic Diagram

Centrality

Density

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Cluster: Violin

performing groups--small ensembles

instruments--string (violin family)

performers--violin

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Strategic Diagram

Centrality

Density

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Cluster: Antiquity

instruments--percussion (bells)

antiquity

temperament and tuning

Greece

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Strategic Diagram

Centrality

Density

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Cluster: Performance

ensemble playing

performance

instrumental playing

psychology

medicine--by topic

practicing and rehearsing

aptitude and ability

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Strategic Diagram

Centrality

Density

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Cluster: Analysis

computer applications

counterpoint

creative process

Stravinsky Igor

analysis

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Strategic Diagram

Centrality

Density

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Cluster: Theory

modality intervals

theory scales

mathematicstheorists

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Strategic Diagram

Centrality

Density

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Cluster: Black studies

sexuality and gender

women's studies

hip hop

United States of America

song texts

black studies

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Strategic Diagram

Centrality

Density

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Cluster: Iconography

instruments

visual and plastic arts

nature

iconography

symbolism

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Future Work

I Use more of the indexing string

I User data

I Mapping the movement of clusters through the strategicdiagram over time

I Produce an online tool for scholars to browse

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Thank You!