MCSN Thursday,08-Sep-11

Introduction

• Understanding the course title: "Topics in Ethnomusicology: Music culture as a social network", and Social Network Analysis
  • Ethnomusicology: the study of global music culture
  • What is music culture? Ethnomusicology takes a broad definition including at least four aspects - the:
    • social: music relations and practices, from individual to group, over time
    • semantic: discourses, concepts and meanings of music
    • phenomenological: experiences and emotions in music performance
    • sonic: musical form and content
  • What is a social network (SN)? What is social network analysis? (SNA)
    • SNA uses graph theory to model social phenomena.
    • Graph: set of vertices (nodes) and lines (links) (abstract)
    • Network: graph with additional information and real-world interpretation (concrete)
    • Social network: network carrying social interpretation (vertices and lines are "social")
    • The theory and method of SN research is called "Social network analysis" (SNA)
  • Why SNA?
    • Traditional concepts used to describe social structures--the aggregate of social relations--are vague, macro, and often ideologically a priori (e.g. "society", "class", "government", "university")
    • The concept of SN allows us to make social structure precise by defining social relations precisely.
  • What is a music network (MN)?
    • A network carrying musical interpretation (vertices and lines are "musical")
    • All four aspects can be modelled as networks
  • SN + MN = MSN

• SNA
  • Theory of Graphs, and modelling social groups
    • What is a graph? Some terms.
      • Node, vertex
      • Link, edge, arc
    • Social groups as graphs (social networks)
      • Nodes represent social entities
      • Links represent relations between social entities
      • Properties of nodes and links:
        • Network properties
        • Attribute properties
      • Examples
        • Mathematica demo
        • Small world network: Six degrees of Kevin Bacon

• • Methods
    • Data collection
    • Data analysis
    • Statistical measures
    • Exploration vs variable relations
    • Importance of visualization
    • Software: Pajek: download and install
    • Ethical problems in SNA methodology
  • Brief history of SNA
• Ethnomusicology via network analysis: examples
  • Musical networks (MNs)
    • Modal cells - e.g. Arabic maqamat
    • Rhythmic cells
    • "Electrical networks" composition
    • Algorithmic composition using Markov chains
  • Musical Social Networks (MSNs)
    • UofA Dept of Music as a social network
    • Musical celebrity and the impact of mediation
    • Twitterverse
    • Meta-ethnomusicology (ESN)
  • Your research in MCSN

1. Defining a relevant phenomenon
2. Formulating a naive research question (how? what? why?)
3. Theorizing the question using a model derived from SNA theory
   1. exploratory research
   2. variable analysis research (comparing networks, or relating network and attribute variables within a single network)
4. Designing a feasible research method to answer the question

Course mechanics

• Wiki: for course outline, resources, lecture notes, your collective contributions. See especially the MCSN 2011 schedule (linked from the main page), and take note of instructions at the top of that page.
• Moodle: for uploading assignments
• Tuesdays: more lecturing, presenting material, answering questions.
• Thursdays: more review, demos, discussions, brainstorming...
• Self-guided days, facilitators
• Pajek: practice makes perfect!
  • Installing
  • Using
  • Pajek help
• ESNAP: primary textbook
• participation, including attendance, and demos (Thurs).
• chapter exercises, questions (due Thurs), assignments (due Tues)
• grading; late and missed work policies
• Course outline: bit.ly/mcsn
• Course expectations
  • Reading and exercises
  • Homework
  • Quizzes
  • Research paper

Homework

• Install Pajek on your computer, download datasets.
• Social structure. Read ESNAP Preface, p. 1, and sections 1.1 to 1.3.2. Try all the Pajek applications.
• Read Robin Wilson, Introduction to Graph Theory, ch. 1 (to be distributed) and do the exercises at the end of the chapter.
• Brainstorm: your examples of MCSN with research questions