Difference between revisions of "Music culture as a social network (Fall 2019)"

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''short link:  http://bit.ly/mcsn19''
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short link to this page:  http://bit.ly/mcsn19<br>
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[https://eclass.srv.ualberta.ca/course/view.php?id=52687 link to eClass site]: http://bit.ly/mcsn19e<br>
 +
[https://bit.ly/mcsn19a link to assignments page]:  http://bit.ly/mcsn19a<br>
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[https://bit.ly/mcsn19g link to google drive folder containing additional resources]:  http://bit.ly/mcsn19g
  
MUSIC 466/566: Music Culture as a Social Network <br>
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'''MUSIC 466/566: Music Culture as a Social Network (Topics in Ethnomusicology)'''<br>
 
 
''Note: this page is still under construction! Absent links may be found at the [https://www.artsrn.ualberta.ca/fwa_mediawiki/index.php/Music_culture_as_a_social_network_(Fall_2011) 2011] version of this course.
 
For any questions please contact [mailto:michaelf@ualberta.ca Michael Frishkopf]
 
  
 
''(available for undergraduate or graduate credit)''
 
''(available for undergraduate or graduate credit)''
'''There are no prerequisites for this course. Anyone can take it.'''
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''There are no prerequisites for this course. Anyone can take it.''
  
 
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Meetings: Tuesday and Thursday, 11:00 AM - 12:20 PM in '''Rutherford South computer lab 2-05A (2nd floor)''' '''NOTE: NEW ROOM!!''' ''Rutherford south is the *old* building.''
Meetings: Tuesday and Thursday, 11:00 AM - 12:20 PM in Old Arts room #118
 
  
 
[[Image:MCSN-poster-small.png|thumb|1600px|right|border|]]
 
[[Image:MCSN-poster-small.png|thumb|1600px|right|border|]]
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Professor [http://frishkopf.org Michael Frishkopf]<br>
 
Professor [http://frishkopf.org Michael Frishkopf]<br>
 
Office: 334D Old Arts Building<br>
 
Office: 334D Old Arts Building<br>
Office hours:  [http://frishkopf.org by appointment] <br>
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'''Office hours:  [https://www.artsrn.ualberta.ca/fwa_mediawiki/index.php/Michael_Frishkopf_office_hours by appointment; click here]''' <br>
 
Tel: 780-492-0225<br>
 
Tel: 780-492-0225<br>
 
Email: michaelf@ualberta.ca<br>
 
Email: michaelf@ualberta.ca<br>
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<br>
 
<br>
  
= Blurb =  
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= Summary =  
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Ethnomusicology is often defined as “the study of music in or as society or culture”. Social Network Analysis (SNA) is an application of mathematics (graph theory) to sociocultural phenomena. As SNA provides an insightful approach towards understanding society (social links) and culture (semantic links), it follows that SNA also provides an insightful means of thinking in ethnomusicology, and a productive tool for ethnomusicological research. Similarly, graph theory has been applied in many other disciplines - from computer science, to physics, to biology - resulting in a flourishing new field generally known as "network science".
  
Ethnomusicology is the study of music in or as society and culture...As social network analysis (SNA) provides an important approach towards understanding society (social linkages) and culture (semantic linkages), then it follows that SNA also provides an insightful means of thinking in ethnomusicology, and a productive tool for ethnomusicological research. In this course we consider ethnomusicology as "the study of music in or as networks." With this formulation, networks define music's social and cultural context; the channels through which music, musical knowledge, and knowledge of music makers, diffuse; and the very substance of music itself. Students will learn about social network analysis in theory and practice, with applications to music, and will conduct a small research project in this domain.
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In this course we consider ethnomusicology as “the study of music in, as, or generating networks.With this formulation, networks define the social and cultural contexts within which music operates; the channels through which music, musical artifacts, and knowledge about music, diffuse; and as the basis for musical performance. Music is also a key factor in the formation and maintenance of social networks. This network approach has become especially pertinent with the rise of social media, at whose core lies a network, and through which much music and musical knowledge or opinion passes.  
  
 +
There are no prerequisites for this course. Anyone can take it.
  
= Overview =
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= Background =
 
[[Image:SNA_segment.png|thumb|400px|right|border|]]
 
[[Image:SNA_segment.png|thumb|400px|right|border|]]
 
These days, [https://secure.wikimedia.org/wikipedia/en/wiki/Social_network social networks] seem to be everywhere, especially with the advent of "social networking" as a catchphrase;  web-based [https://secure.wikimedia.org/wikipedia/en/wiki/Social_networking social networking services] such as Facebook, Twitter, YouTube, and Instagram; and popularization of social network concepts such as [https://secure.wikimedia.org/wikipedia/en/wiki/Six_degrees_of_separation six degrees of separation], and [https://secure.wikimedia.org/wikipedia/en/wiki/Small-world_network small-world networks][http://mathworld.wolfram.com/SmallWorldNetwork.html]. But the idea of using [https://secure.wikimedia.org/wikipedia/en/wiki/Graph_theory graph theory] to understand social groups and culture goes back nearly a century, while social networks themselves are intrinsic to being human. [http://www.sciencemag.org/content/323/5916/892.full?ijkey=UI5HJUxfOqIKc&keytype=ref&siteid=sci][https://encrypted.google.com/url?sa=t&source=web&cd=15&ved=0CCQQFjAEOAo&url=http%3A%2F%2Fwww.pbs.plym.ac.uk%2Fmi%2Fpdf%2F17-04-09%2F1.%2520Crossley%2520et%2520al%2520intro%25201-7.pdf&ei=HDiKTZ3TD4e6sAOnpvGQDA&usg=AFQjCNHpm4oTFjpvul2r3PQYzjJfvqDqdg]
 
These days, [https://secure.wikimedia.org/wikipedia/en/wiki/Social_network social networks] seem to be everywhere, especially with the advent of "social networking" as a catchphrase;  web-based [https://secure.wikimedia.org/wikipedia/en/wiki/Social_networking social networking services] such as Facebook, Twitter, YouTube, and Instagram; and popularization of social network concepts such as [https://secure.wikimedia.org/wikipedia/en/wiki/Six_degrees_of_separation six degrees of separation], and [https://secure.wikimedia.org/wikipedia/en/wiki/Small-world_network small-world networks][http://mathworld.wolfram.com/SmallWorldNetwork.html]. But the idea of using [https://secure.wikimedia.org/wikipedia/en/wiki/Graph_theory graph theory] to understand social groups and culture goes back nearly a century, while social networks themselves are intrinsic to being human. [http://www.sciencemag.org/content/323/5916/892.full?ijkey=UI5HJUxfOqIKc&keytype=ref&siteid=sci][https://encrypted.google.com/url?sa=t&source=web&cd=15&ved=0CCQQFjAEOAo&url=http%3A%2F%2Fwww.pbs.plym.ac.uk%2Fmi%2Fpdf%2F17-04-09%2F1.%2520Crossley%2520et%2520al%2520intro%25201-7.pdf&ei=HDiKTZ3TD4e6sAOnpvGQDA&usg=AFQjCNHpm4oTFjpvul2r3PQYzjJfvqDqdg]
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On a more theoretical level, we'll explore the co-mediation of social networks (sonets) and semantic networks (senets) as providing the basic fabric of social and cultural life.
 
On a more theoretical level, we'll explore the co-mediation of social networks (sonets) and semantic networks (senets) as providing the basic fabric of social and cultural life.
 +
= [https://drive.google.com/open?id=16zgeyhUdAiGbP7uOLyOc5BqHkgnEiVSA Official course syllabus] =
  
= Schedule =
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[https://drive.google.com/open?id=16zgeyhUdAiGbP7uOLyOc5BqHkgnEiVSA Official course syllabus]
  
[[MCSN 2019 schedule]] (assignments and class activities, by date)
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= Schedule of Assignments =
  
[https://www.google.com/calendar/hosted/ualberta.ca/render?cid=OTl1Zm9hbTgzamlvN3Qxa3JuODZhazVxMzRAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ Google Calendar]
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[[MCSN 2019 schedule]] (assignments and class activities, by date) <br>
 +
Short link:  http://bit.ly/mcsn19a
  
= Requirements =
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The schedule will be developed as the course progresses, in consultation with students and according to student feedback.  See http://bit.ly/mcsn19a for the latest updates. New assignments will be posted the previous week.
  
* Weekly...
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This course schedule includes three parallel ''streams'':
** Classroom work:  Lectures (mostly Tuesdays), demos (your demonstrations of Pajek technique), and discussions (more on Thursdays), all interspersed with group exercises, Q/A, videos, demos, etc.
 
** Homework, promoting a theoretical and practical grasp of social network concepts 
 
*** Readings: (theory and methods in [https://www-cambridge-org.login.ezproxy.library.ualberta.ca/core/books/exploratory-social-network-analysis-with-pajek/6F8EE2512CB7C6D233DB2DAC3886D4F5 ESNAP], 3rd edition (2018), and case studies of applications to music culture)
 
*** Lab:  Pajek exercises, described in the ESNAP text (it's very important to do these completely!)
 
*** Problems: to test and reinforce those concepts. ''Questions'' are typically due on Thursdays; ''assignments'' are typically due the following Tuesday.
 
* Occasional in-class self-guided group projects (these ''projects'' are to be written up and handed in the following class)
 
* Three very short (20 minute) quizzes, to motivate and assess learning
 
* Proposal to analyze a public online social network, comprising five short paragraphs and a bibliography (draft to be resubmitted until accepted):
 
  
# Identify: Identify a phenomenon from MCSN.  Discuss the general aim and value of your study, framed as a contribution to ethnomusicology. 
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# SNA stream: Learning SNA, its theory (what), motivation (why), and mechanics (how - using Pajek), with homework, and in-class lecture/workshop formats;
# Contextualize: Provide background (topical and theoretical), citing relevant literature
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# Critical stream: discussing applications of SNA to music and culture, via review of articles, book chapters, datasets, through homework and in-class seminar discussion format;
# Query: List a few research questions inquiring about this phenomenon. What do you want to understand? Provide tentative hypotheses if you have any.
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# Project stream: including identifying research problem and data; finding and reviewing sources; preparing proposal, annotated bibliography, outline, presentation, and final paper, including also in-class discussions of work in progress.   
# Model: Theorize your questions using SNA to model the phenomenon. How can you frame the question in terms of social networks? Cite relevant literature, if appropriate.
 
# Method: What sort of procedure can you propose for gathering data, analyzing it (with Pajek), and answering the questions? Cite relevant literature, if appropriate.
 
# Bibliography (can be short at this initial stage), including web sitesYou may find that [http://www.insna.org/ INSNA] contains useful sources, but your bibliography can include musical as well as SNA materials.
 
  
* SNA research project of your choosing, including planning, written proposal, data gathering, preparation of Pajek files, analysis, interpretation, and writeup as a final paper (Music 466: 2500 words; Music 566: 3500 words).
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{| class="wikitable"
* Class presentation, amply illustrated with Pajek graphs - 10 minutes - outlining your project's main questions and methods, with partial results, during the last few classes at term's end (depending on enrollment).
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! !! SNA stream (Tuesdays) !! Critical Stream (Thursdays) !! Project Stream (Thursdays)
 
+
|-
Note that there is no final exam, but only a final paper. All assignments are to be handed in via the [https://eclass-sandbox.srv.ualberta.ca/my/ Moodle], but please bring them to class also (electronically or hard copy) for discussion. The final paper should be submitted electronically, and also in hardcopy.
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! At home, prior to class
 
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| ESNAP reading and problem sets || Other readings, reading reviews || Preparation of ideas, examples, assignments
If possible, bring your laptop to each class, so we can explore the software together.
 
 
 
Notes:
 
   
 
# This course can be taken at either of two levels:  466 (regular) or 566 (advanced). If you are an undergraduate, you should be enrolled in 466. Graduate students should be enrolled in 566. At the same grade level, expectations for 566 are slightly higher, and the final paper should display greater breadth and sophistication in working with the literature (as well as being 50% longer).
 
# Word counts do not including bibliography or illustrative graphs and other diagrams.
 
 
 
= Evaluation =
 
 
 
The evaluation of each requirement is on a scale from 0-4 points.  These scores are combined according to the percentages indicated in order to produce a final numeric grade. This grade is rounded to the nearest numeric value in the table below, in order to determine the final letter grade. In exceptional cases the grade A+ may also be assigned.  Expectations for the 500 level are higher than for the 400 level. ''Without a valid excuse (documented medical or family emergency) grades for late assignments will decremented by a quarter-point per day, and make-up quizzes will not be administered.''  Please take care to plan ahead, bearing in mind due dates for your other courses.
 
 
 
All assignments are to be submitted via the [https://eclass-sandbox.srv.ualberta.ca/my/ Moodle].
 
 
 
* Attendance and class participation (including Pajek demos): 15%
 
* Homework (mainly ESNAP "questions" and "assignments", as well as project writeups): 20% total (each submitted item receives an equal weight).
 
* Quizzes: 6.6666% each (20% total)
 
* Project proposal: 5%
 
* Research class presentation: 10%
 
* Research paper:  30%
 
 
 
 
 
{|border="1" align="left" style="text-align:center;"
 
|A
 
|A-
 
|B+
 
|B
 
|B-
 
|C+
 
|C
 
|C-
 
|D+
 
|D
 
|F
 
 
|-
 
|-
|4.0
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! In class
|3.7
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| Lectures and labs || Discussions about readings, quizzes || Brainstorming and brief reports, with class feedback
|3.3
 
|3.0
 
|2.7
 
|2.3
 
|2.0
 
|1.7
 
|1.3
 
|1.0
 
|0.0
 
 
|}
 
|}
  
<br>
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= Requirements =
<br>
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<br>
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See [https://drive.google.com/open?id=16zgeyhUdAiGbP7uOLyOc5BqHkgnEiVSA Official course syllabus]
  
 
= eClass =
 
= eClass =
  
eClass will be used to accept assignments.  Please do not email assignments or submit hardcopy.
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[https://eclass.srv.ualberta.ca/course/view.php?id=52687 eClass] will be used to accept assignments.  Please do not email assignments or submit hardcopy. Note the shortcut:  http://bit.ly/mcsn19e
  
 
= Resources =
 
= Resources =
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All print materials on Rutherford Reserve, and several are available free online (you don't have to buy anything!):
 
All print materials on Rutherford Reserve, and several are available free online (you don't have to buy anything!):
  
* Wouter de Nooy, Andrej Mrvar, and Vladimir Batagelj, ''[https://search.library.ualberta.ca/catalog/8303932 Exploratory Social Network Analysis with Pajek]'' (abbreviated: ESNAP), 3rd edition. (Cambridge University Press, 2018). (Available [https://search.library.ualberta.ca/catalog/8303932 online] and in the SUB bookstore.)  To be read in conjunction with the free SNA software package [http://mrvar.fdv.uni-lj.si/pajek/ Pajek] (which was created for PCs but also runs fine on Macs; [http://mrvar.fdv.uni-lj.si/pajek/MAC/PajekOSX1.pdf installation instructions for Mac are here]).
+
* Wouter de Nooy, Andrej Mrvar, and Vladimir Batagelj, ''[https://search.library.ualberta.ca/catalog/8303932 Exploratory Social Network Analysis with Pajek]'' (abbreviated: ESNAP), 3rd edition. (Cambridge University Press, 2018). (Available [https://search.library.ualberta.ca/catalog/8303932 online] and in the SUB bookstore.)  To be read in conjunction with the free SNA software package [http://mrvar.fdv.uni-lj.si/pajek/ Pajek] (which was created for PCs but also runs fine on Macs; [[Pajek installation | installation instructions are here]]).  Please download the [http://mrvar.fdv.uni-lj.si/pajek/be3.htm book's associated datasets]; you'll need to work with them as you read the text and follow its hands-on instructions.
 +
* Nick Crossley, Siobhan McAndrew, Paul Widdop, eds. [https://www-taylorfrancis-com.login.ezproxy.library.ualberta.ca/books/e/9781315867793 Social networks and music worlds].
 +
* Albert-László Barabási, [http://networksciencebook.com/ Network Science]
 
* Paul McLean, ''[https://ezpa.library.ualberta.ca/ezpAuthen.cgi?url=https://ebookcentral.proquest.com/lib/ualberta/detail.action?docID=4761544 Culture in Networks]''
 
* Paul McLean, ''[https://ezpa.library.ualberta.ca/ezpAuthen.cgi?url=https://ebookcentral.proquest.com/lib/ualberta/detail.action?docID=4761544 Culture in Networks]''
* Guido Caldarelli, Michele Catanzaro, ''Networks: A Very Short Introduction'', OUP Oxford, Oct 25, 2012 [https://www.amazon.com/Networks-Very-Short-Introduction-Introductions-ebook/dp/B00A18MV94/ref=tmm_kin_swatch_0?_encoding=UTF8&qid=1556160050&sr=8-1-fkmrnull Available as an e-book]
 
 
* Raphaël Nowak, Andrew Whelan, editors, ''[https://search.library.ualberta.ca/catalog/7663305 Networked music cultures : contemporary approaches, emerging issues]''
 
* Raphaël Nowak, Andrew Whelan, editors, ''[https://search.library.ualberta.ca/catalog/7663305 Networked music cultures : contemporary approaches, emerging issues]''
* Nick Crossley, Siobhan McAndrew, Paul Widdop, eds. [https://www-taylorfrancis-com.login.ezproxy.library.ualberta.ca/books/e/9781315867793 Social networks and music worlds].
 
  
 
=== Optional===
 
=== Optional===
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''Networks in general''
 
''Networks in general''
 +
* Guido Caldarelli, Michele Catanzaro, ''Networks: A Very Short Introduction'', OUP Oxford, Oct 25, 2012 [https://www.amazon.com/Networks-Very-Short-Introduction-Introductions-ebook/dp/B00A18MV94/ref=tmm_kin_swatch_0?_encoding=UTF8&qid=1556160050&sr=8-1-fkmrnull Available as an e-book] and for sale at SUB bookstore.
 
* Mark Newman. [https://search.library.ualberta.ca/catalog/8511958 Networks] (second edition), esp. Chapter 4 on Social Networks and Part II on fundamentals of network theory.
 
* Mark Newman. [https://search.library.ualberta.ca/catalog/8511958 Networks] (second edition), esp. Chapter 4 on Social Networks and Part II on fundamentals of network theory.
  
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=== Required ===
 
=== Required ===
  
[[Pajek]] (Slovenian for "spider") is required, as it accompanies our textbook.  Pajek runs on Windows, Linux, and Intel Mac platforms. Your first task is to [[Pajek installation | install Pajek on your computer]], and begin to get comfortable using it.  [[Pajek help|Help]] is available.  Note that Pajek runs best on PCs, but can also easily be run on a Mac with a bit of prep. I'll help you through it.
+
[[Pajek]] (Slovenian for "spider") is required, as it accompanies our textbook.  Pajek runs on Windows, Linux, and Intel Mac platforms. [[Pajek installation | Pajek installation instructions are here]]. Install and begin to get comfortable using it.  [[Pajek help|Help]] is available.  Note that Pajek runs best on PCs, but can also easily be run on a Mac with a bit of prep. I'll help you through it.
 
 
Generally, the easiest way to get around the Mac/PC issues for Mac users is to run Windows on your Mac. You can use Bootcamp to do this for free, or invest in a student-discounted version of [https://www.parallels.com/blogs/student-discount-on-parallels-desktop-for-mac/ Parallels].
 
 
 
===Optional Network analysis and visualization tools===
 
 
 
See also http://en.wikipedia.org/wiki/Network_science#Network_analysis_and_visualization_tools
 
 
 
Optionally, you may like to explore and experiment with [http://en.wikipedia.org/wiki/Category:Graph_drawing_software other packages]...
 
 
 
[http://socnetv.org/ SocNetV]
 
 
 
[http://visone.info/ Visone]
 
 
 
[http://www.sagemath.org/ Sage]
 
 
 
[http://nodexl.codeplex.com/ NodeXL] for Excel (mainly Windows - but there are [http://www.connectedaction.net/2010/11/16/how-to-run-nodexl-on-a-connected-mac-or-other-platform-using-amazon-ec2/ solutions for mac] too)
 
 
 
[http://gephi.org/ gephi]
 
 
 
[http://www.graphviz.org/ graphviz]
 
 
 
[http://www.cytoscape.org/ cytoscape]
 
 
 
[http://graph-tool.skewed.de/ Graph-tool]
 
 
 
[http://www.touchgraph.com/seo touchgraph]
 
 
 
[http://igraph.org/ igraph]
 
 
 
[http://www.analytictech.com/netdraw/netdraw.htm netdraw]
 
 
 
[http://graphexploration.cond.org/ GUESS]
 
 
 
[http://www.stanford.edu/group/sonia/ Sonia]
 
 
 
[http://orange.biolab.si/ Orange], for data visualization, analysis, mining...
 
 
 
[https://www.amii.ca/meerkat/ Meerkat]
 
 
 
[http://snap.stanford.edu/ SNAP]
 
 
 
[http://semoss.org/ SEMOSS]
 
 
 
[[Zeppelin]]
 
 
 
[https://sourceforge.net/projects/egonet/ Egonet]
 
 
 
Others:
 
* [http://www.casos.cs.cmu.edu/tools/index.php Tools at Carnegie Mellon's CASOS]
 
*[[Graph-tool]] and [[NetworkX]], [[Free Software|free]] and efficient Python modules for manipulation and statistical analysis of networks. [http://graph-tool.skewed.de/] [http://networkx.lanl.gov/]
 
* [http://www.texample.net/tikz/ tikz, which produces graphs from latex code]
 
*[http://igraph.sourceforge.net igraph], an [[open source]] [[C (programming language)|C]] library for the analysis of large-scale complex networks, with interfaces to [[R (programming language)|R]], [[Python (programming language)|Python]] and [[Ruby (programming language)|Ruby]].
 
*[[Orange (software)|Orange]], a free data mining software suite, module [http://www.ailab.si/orange/doc/modules/orngNetwork.htm orngNetwork]
 
*[http://pajek.imfm.si/doku.php Pajek], program for (large) network analysis and visualization.
 
*[[Tulip (software)|Tulip]], a free data mining and visualization software dedicated to the analysis and visualization of relational data. [http://tulip.labri.fr/]
 
*[http://semoss.org/ SEMOSS], an [[RDF_query_language|RDF-based]] [[Open-source_software|open source]] context-aware analytics tool written in [[Java_(programming_language)|Java]] leveraging the [[SPARQL]] query language.
 
*[http://casos.cs.cmu.edu/projects/ora/ ORA], a tool for [[Dynamic Network Analysis]] and network visualization. <ref>Kathleen M. Carley, 2014, ORA: A Toolkit for Dynamic Network Analysis and Visualization, In Reda Alhajj and Jon Rokne (Eds.) Encyclopedia of Social Network Analysis and Mining, Springer.</ref>
 
*[https://www.nsnam.org/ NS-3], a network simulation system
 
  
==[[Research on music networks]]==
+
Generally, the most straightforward way to get around the Mac/PC issues for Mac users is to run Windows on your Mac. You can use Bootcamp to do this for free, or invest in a student-discounted version of [https://www.parallels.com/blogs/student-discount-on-parallels-desktop-for-mac/ Parallels] or use free VMware.  In these cases you'll have to have a copy of Windows, but there's a free option too. And then there's Wine, which allows you to run Windows apps on your Mac without running Windows. It's a simpler workaround and it works. See installation link above for the details.
  
[[Research on music networks | types of music network, kinds of research]]
+
A very useful "helper" program is [http://www.pfeffer.at/txt2pajek/index.php txt2pajek], which converts text files that name nodes into proper Pajek files that reference nodes by number. There's [http://www.pfeffer.at/txt2pajek/txt2pajek.pdf online help] available.
  
== Pajek datasets for ESNAP ==
+
===Other network analysis and visualization tools===
  
Download these [http://vlado.fmf.uni-lj.si/pub/networks/data/esna/default.htm sample data sets] for use with the textbook, ESNAP. Store them in your Pajek Data directory for future use.
+
* Optionally, you may like to explore and experiment with these [[Packages for network analysis, simulation, and visualization | packages for network analysis, simulation, and visualization]]...
 +
* See also [http://en.wikipedia.org/wiki/Network_science#Network_analysis_and_visualization_tools current wikipedia listing of network science tools], and [http://en.wikipedia.org/wiki/Category:Graph_drawing_software graph drawing], and [https://en.wikipedia.org/wiki/Graph_database graph databases]
  
== SNA Datasets, including those relevant to music ==
+
==[[Research on music networks |Performing research on music networks]]==
  
* [https://github.com/awesomedata/awesome-public-datasets/blob/master/README.rst#complexnetworks Public datasets]
+
[[Research on music networks | Click here to see useful information and listings of various kinds: types of music network, research questions, data sources, methods, and bibliography...]]
* [http://konect.cc/networks/ The KONECT Project network list][http://konect.uni-koblenz.de/networks/]
 
* [http://konect.cc/networks/arenas-jazz/ Jazz musician network]
 
* [http://alllmusic.com Allmusic, containing network data regarding collaborations and styles]
 
* http://www-personal.umich.edu/~mejn/netdata/
 
* http://deim.urv.cat/~aarenas/data/welcome.htm
 
* http://snap.stanford.edu/data/index.html#road
 
  
==Other resources==
+
==Other SNA resources==
  
* [[SNA websites]]
+
* [[Network Science & SNA websites]] (centres, organizations, projects, courses)
* [[SNA applications]]
+
* [[Network Science & SNA conferences]]
* [[SNA demos]]
+
* [[SNA syllabi]] (from other universities)
 +
* [[SNA sample analyses]]
 +
* [[Network simulations | SNA simulations and demos]]
 
* [[SNA videos]]
 
* [[SNA videos]]
* [[SNA data]]
+
* [[Statistics]] (general)
* [http://ccl.northwestern.edu/netlogo/resources.shtml Netlogo] for network simulations
+
* [[Semantic music webs]]
* [[Statistics]]
 
* [[SNA syllabi]]
 
* [[SNA datasets]]
 
  
 
= Help pages =
 
= Help pages =

Latest revision as of 19:15, 19 November 2019

short link to this page: http://bit.ly/mcsn19
link to eClass site: http://bit.ly/mcsn19e
link to assignments page: http://bit.ly/mcsn19a
link to google drive folder containing additional resources: http://bit.ly/mcsn19g

MUSIC 466/566: Music Culture as a Social Network (Topics in Ethnomusicology)

(available for undergraduate or graduate credit) There are no prerequisites for this course. Anyone can take it.

Meetings: Tuesday and Thursday, 11:00 AM - 12:20 PM in Rutherford South computer lab 2-05A (2nd floor) NOTE: NEW ROOM!! Rutherford south is the *old* building.

MCSN-poster-small.png

Professor Michael Frishkopf
Office: 334D Old Arts Building
Office hours: by appointment; click here
Tel: 780-492-0225
Email: michaelf@ualberta.ca


Summary

Ethnomusicology is often defined as “the study of music in or as society or culture”. Social Network Analysis (SNA) is an application of mathematics (graph theory) to sociocultural phenomena. As SNA provides an insightful approach towards understanding society (social links) and culture (semantic links), it follows that SNA also provides an insightful means of thinking in ethnomusicology, and a productive tool for ethnomusicological research. Similarly, graph theory has been applied in many other disciplines - from computer science, to physics, to biology - resulting in a flourishing new field generally known as "network science".

In this course we consider ethnomusicology as “the study of music in, as, or generating networks.” With this formulation, networks define the social and cultural contexts within which music operates; the channels through which music, musical artifacts, and knowledge about music, diffuse; and as the basis for musical performance. Music is also a key factor in the formation and maintenance of social networks. This network approach has become especially pertinent with the rise of social media, at whose core lies a network, and through which much music and musical knowledge or opinion passes.

There are no prerequisites for this course. Anyone can take it.

Background

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These days, social networks seem to be everywhere, especially with the advent of "social networking" as a catchphrase; web-based social networking services such as Facebook, Twitter, YouTube, and Instagram; and popularization of social network concepts such as six degrees of separation, and small-world networks[1]. But the idea of using graph theory to understand social groups and culture goes back nearly a century, while social networks themselves are intrinsic to being human. [2][3]

The same "network" concept is also used to define "semantic networks" of meaning, using the same analytical techniques that apply to networks of all kinds: locating centers, delineating cohesive subgroups, assessing connectivity, and related operations. In this course we examine both social networks (sonets) and semantic networks (senets), as the basis for doing ethnomusicology.

Ethnomusicology is typically defined as the study of music in society or the study of music as culture...if social network analysis (SNA) is an important approach towards understanding society and culture, then it follows that SNA should also provide an insightful means of thinking in ethnomusicology, and a productive tool for ethnomusicological research: Ethnomusicology is the study of music in social networks. Social networks define music's social and cultural context, as well as the channels through which music, musical knowledge, and knowledge of music makers, diffuse.

Yet few ethnomusicologists have explored SNA's possibilities, perhaps because SNA appears inaccessible, filed under "mathematical sociology," while music scholars have tended to prefer the more qualitative, critical, and interpretive approaches of the human sciences. SNA also presents some challenging methodological difficulties for fieldworkers - mapping social networks is not always easy, practically and ethically. Yet SNA's origins lies in social anthropology, a field with longstanding connections to ethnomusicology. Methodologically SNA is more feasible today, with the emergence of online virtual communities, defined by social networking websites, and other electronic communications. And the basic mathematics required to understand SNA is quite elementary.

This seminar-workshop attempts to bridge the gap between traditional humanistic scholarship and SNA by providing a gentle introduction to methods, theories, and issues in social network analysis,with applications to ethnomusicology. You won’t merely read about social network analysis, you’ll actually do it!

Ethnomusicological applications of SNA include understanding the ways musicians and audiences interact in performance; network aspects of celebrity formation; exploring communities of musical taste; understanding the circulation of online music; analyzing the role of music in shaping social networks, particularly online (including those specifically devoted to music); investigating networks of musical friendship, prestige, and respect; examining linkages between music sites on the Internet; considering networks generated by musical collaborations (e.g. composer-lyricist relations); the overlap of friendship and musical collaboration network; small world networks in the arts (c.f. Degrees of Kevin Bacon[4]); affiliation networks of numerous types; the use of social networks to promote music and musicians, and many other topics.

On a more theoretical level, we'll explore the co-mediation of social networks (sonets) and semantic networks (senets) as providing the basic fabric of social and cultural life.

Official course syllabus

Official course syllabus

Schedule of Assignments

MCSN 2019 schedule (assignments and class activities, by date)
Short link: http://bit.ly/mcsn19a

The schedule will be developed as the course progresses, in consultation with students and according to student feedback. See http://bit.ly/mcsn19a for the latest updates. New assignments will be posted the previous week.

This course schedule includes three parallel streams:

  1. SNA stream: Learning SNA, its theory (what), motivation (why), and mechanics (how - using Pajek), with homework, and in-class lecture/workshop formats;
  2. Critical stream: discussing applications of SNA to music and culture, via review of articles, book chapters, datasets, through homework and in-class seminar discussion format;
  3. Project stream: including identifying research problem and data; finding and reviewing sources; preparing proposal, annotated bibliography, outline, presentation, and final paper, including also in-class discussions of work in progress.
SNA stream (Tuesdays) Critical Stream (Thursdays) Project Stream (Thursdays)
At home, prior to class ESNAP reading and problem sets Other readings, reading reviews Preparation of ideas, examples, assignments
In class Lectures and labs Discussions about readings, quizzes Brainstorming and brief reports, with class feedback

Requirements

See Official course syllabus

eClass

eClass will be used to accept assignments. Please do not email assignments or submit hardcopy. Note the shortcut: http://bit.ly/mcsn19e

Resources

Books

You'll find a number of these books on reserve in the Music Library (Rutherford, 2nd floor), though new rules may preclude placing textbooks there. Some are also available electronically. But I do recommend purchasing the required work (ESNAP), since working from an electronic version may prove awkward as you're also using your computer to work the examples using Pajek.

Required

All print materials on Rutherford Reserve, and several are available free online (you don't have to buy anything!):

Optional

No need to purchase these at the outset, and several are already available for free online. As for the others, if you find them to your liking you may wish to own a copy. Browse at the library or bookstore.

Texts and reference works

We may use these works to supplement the primary text. I'll make assignments from some of them from time to time; others are listed simply for your reference.

Networks in general

  • Guido Caldarelli, Michele Catanzaro, Networks: A Very Short Introduction, OUP Oxford, Oct 25, 2012 Available as an e-book and for sale at SUB bookstore.
  • Mark Newman. Networks (second edition), esp. Chapter 4 on Social Networks and Part II on fundamentals of network theory.

Social Network Analysis

  • Robert A. Hanneman and Mark Riddle. Introduction to social network methods (also available as a pdf. Free.) Works well with Netdraw (which runs only on PCs, or Macs in Windows compatibility mode). You may wish to refer to this alternative text to clarify and reinforce understanding, especially if you're having trouble with a concept presented in ESNAP.
  • John P Scott, Social Network Analysis: A Handbook, 2nd ed. (Sage Publications Ltd, 2000). (Available in the SUB bookstore.) Provides a succinct summary of the field at a more advanced level.
  • Wasserman, Stanley and Faust, Katherine. Social network analysis: methods and applications. Cambridge, New York: Cambridge University Press; 1994. A rich summary of SNA theory and applications, for those who want a more complete and rigorous reference work.

Graph theory

Popular treatments

Enjoyable and accessible, these books will also stimulate your creative thinking...feel free to browse selectively.

(Social) Network Analysis Software (all free!)

Required

Pajek (Slovenian for "spider") is required, as it accompanies our textbook. Pajek runs on Windows, Linux, and Intel Mac platforms. Pajek installation instructions are here. Install and begin to get comfortable using it. Help is available. Note that Pajek runs best on PCs, but can also easily be run on a Mac with a bit of prep. I'll help you through it.

Generally, the most straightforward way to get around the Mac/PC issues for Mac users is to run Windows on your Mac. You can use Bootcamp to do this for free, or invest in a student-discounted version of Parallels or use free VMware. In these cases you'll have to have a copy of Windows, but there's a free option too. And then there's Wine, which allows you to run Windows apps on your Mac without running Windows. It's a simpler workaround and it works. See installation link above for the details.

A very useful "helper" program is txt2pajek, which converts text files that name nodes into proper Pajek files that reference nodes by number. There's online help available.

Other network analysis and visualization tools

Performing research on music networks

Click here to see useful information and listings of various kinds: types of music network, research questions, data sources, methods, and bibliography...

Other SNA resources

Help pages

How to write these wiki pages

Pajek help

Official policy

Please carefully review the following:

  • The University of Alberta is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect. Students are particularly urged to familiarize themselves with the provisions of the Code of Student Behaviour and avoid any behaviour which could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts and/or participation in an offence. Academic dishonesty is a serious offence and can result in suspension or expulsion from the University.”