Music culture as a social network (Fall 2019)
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 (2nd floor) NOTE: NEW ROOM!!
- 1 Summary
- 2 Background
- 3 Official course syllabus
- 4 Schedule
- 5 Requirements
- 6 eClass
- 7 Resources
- 7.1 Books
- 7.2 (Social) Network Analysis Software (all free!)
- 7.3 Research on music networks
- 7.4 Pajek datasets for ESNAP
- 7.5 SNA Datasets, including those relevant to music
- 7.6 Other resources
- 8 Help pages
- 9 Official policy
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.
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. 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. 
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); 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.
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:
- SNA stream: Learning SNA, its theory (what), motivation (why), and mechanics (how - using Pajek), with homework, and in-class lecture/workshop formats;
- 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;
- 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, quizzes||Discussions about readings||Brainstorming and brief reports, with class feedback|
eClass will be used to accept assignments. Please do not email assignments or submit hardcopy.
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.
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, Exploratory Social Network Analysis with Pajek (abbreviated: ESNAP), 3rd edition. (Cambridge University Press, 2018). (Available online and in the SUB bookstore.) To be read in conjunction with the free SNA software package Pajek (which was created for PCs but also runs fine on Macs; installation instructions for Mac are here). Please download the 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. Social networks and music worlds.
- Albert-László Barabási, Network Science
- Paul McLean, Culture in Networks
- Raphaël Nowak, Andrew Whelan, editors, Networked music cultures : contemporary approaches, emerging issues
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.
- Linton C. Freeman, The Development of Social Network Analysis: A Study in the Sociology of Science (Empirical Press, 2004). Outlines the intellectual history of SNA.
- 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.
- Peter J. Carrington. Models and methods in social network analysis. Cambridge, New York: Cambridge University Press; 2005. A collection of more advanced papers on SNA. Available electronically via our library.
- Introduction to Graph Theory, by Robin Wilson (4th edition). A gentle introduction. We may only be reading the beginning of this text.
- Introduction to graph theory [electronic resource / Vitaly I. Voloshin]
Enjoyable and accessible, these books will also stimulate your creative thinking...feel free to browse selectively.
- Albert-Laszlo Barabasi, Linked: How Everything Is Connected to Everything Else and What It Means (Plume, 2003).
- Duncan J. Watts, Six Degrees: The Science of a Connected Age (W. W. Norton & Company, 2004).
- Malcolm Gladwell, The Tipping Point: How Little Things Can Make a Big Difference (Back Bay Books, 2002).
- Nicholas A. Christakis and James H. Fowler, Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives (New York: Little, Brown and Company, 2009). (A popular science treatment.)
(Social) Network Analysis Software (all free!)
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 install (here's how), 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.
Optional Network analysis and visualization tools
(broken link? see the 2011 version of the course here).
Optionally, you may like to explore and experiment with other packages...
Orange, for data visualization, analysis, mining...
webweb, to display interactive networks in a browser.
- Tools at Carnegie Mellon's CASOS
- Graph-tool and NetworkX, free and efficient Python modules for manipulation and statistical analysis of networks.  
- tikz, which produces graphs from latex code
- igraph, an open source C library for the analysis of large-scale complex networks, with interfaces to R, Python and Ruby.
- Orange, a free data mining software suite, module orngNetwork
- Pajek, program for (large) network analysis and visualization.
- Tulip, a free data mining and visualization software dedicated to the analysis and visualization of relational data. 
- SEMOSS, an RDF-based open source context-aware analytics tool written in Java leveraging the SPARQL query language.
- 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>
- NS-3, a network simulation system
Pajek datasets for ESNAP
Download these sample data sets for use with the textbook, ESNAP. Store them in your Pajek Data directory for future use.
SNA Datasets, including those relevant to music
- Network repository
- Public datasets
- The KONECT Project network list
- Jazz musician network
- Allmusic, containing network data regarding collaborations and styles
- SNA websites
- SNA applications
- SNA demos
- SNA videos
- SNA data
- Netlogo for network simulations
- SNA syllabi
- SNA datasets
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.”