visualizing the knowledge space of music · 2017-07-04 · goal: map the knowledge space of music i...
TRANSCRIPT
Visualizing the Knowledge Space of MusicIAML 2017, the 66th IAML Congress
Glenn Henshaw, Fan Yun
June 22, 2017
What is music scholarship?
I Music scholarship is hard to defineI Deeply interdiciplinary.I It’s a young field.
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
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
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.
Goal: Map the knowledge space of a given field
I Expert surveys tend to be costly and slow endeavors.
I Expert bias.
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.
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
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.
The Data
I Almost all academic music articles (2000-2015)
I 263,656 Rows
I 59,908 Articles
I 25,297 distinct terms (lvl1)
15 Most common terms
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
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).
From matrix to graph using the matrix CI Despite its beauty, we could not obtain valuable information
from this graph!
From matrix to graph using the matrix C
I High frequency terms dominate the connections.
Cosine similarity
Cosine similarity (CS) is defined as
CS(i , j) =
√C 2ij
CiiCjj.
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.
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.
Hierarchical Clustering (a rough sketch)
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Hierarchical Clustering (a rough sketch)
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Hierarchical Clustering (a rough sketch)
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Hierarchical Clustering (a rough sketch)
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Hierarchical Clustering (a rough sketch)
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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
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
Strategic Diagram
Strategic Diagram
Centrality
Density
Strategic Diagram
Centrality
Density
Cluster: Form
motive and theme
texture
harmony
form
rhythm and meter
tonality
melody
Strategic Diagram
Centrality
Density
Cluster: Popular Recordings
performers--popular music
performing groups--popular music
sound recordings
Strategic Diagram
Centrality
Density
Cluster: Pedagogues
anecdotes reminiscences etc.
performers--piano
pedagogues
academic institutions
Strategic Diagram
Centrality
Density
Cluster: Rock
sociology
rock
cultural studies
popular music
Strategic Diagram
Centrality
Density
Cluster: Mechanical instruments
instruments--collections
instruments--mechanical
Strategic Diagram
Centrality
Density
Cluster: Classical
Haydn Joseph
Mozart Wolfgang Amadeus
Beethoven Ludwig van
Strategic Diagram
Centrality
Density
Cluster: Organ
instruments--keyboard (organ family)
instrument builders--organ
religious institutions
conservation and restoration
Strategic Diagram
Centrality
Density
Cluster: Violin
performing groups--small ensembles
instruments--string (violin family)
performers--violin
Strategic Diagram
Centrality
Density
Cluster: Antiquity
instruments--percussion (bells)
antiquity
temperament and tuning
Greece
Strategic Diagram
Centrality
Density
Cluster: Performance
ensemble playing
performance
instrumental playing
psychology
medicine--by topic
practicing and rehearsing
aptitude and ability
Strategic Diagram
Centrality
Density
Cluster: Analysis
computer applications
counterpoint
creative process
Stravinsky Igor
analysis
Strategic Diagram
Centrality
Density
Cluster: Theory
modality intervals
theory scales
mathematicstheorists
Strategic Diagram
Centrality
Density
Cluster: Black studies
sexuality and gender
women's studies
hip hop
United States of America
song texts
black studies
Strategic Diagram
Centrality
Density
Cluster: Iconography
instruments
visual and plastic arts
nature
iconography
symbolism
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
Thank You!