Attending in person

• Wearing of masks is not required, but is greatly appreciated while in the classroom
• If you have any symptoms of COVID-19 or have been in contact with someone who has tested positive for COVID-19 please stay home (this will not affect your grade in this course)
• It is up to us to make a safe and welcoming learning environment for everyone!

Social structures

• Theoretical tools to think about social processes through the lens of social structures and relational systems

Social network theory

• History and theory of social networks as a way to understand human relations and organization

Network methods

• Methodological tools to produce and consume empirical network analyses

Balancing theory and methods is tricky, but vital for the topics in the class

Syllabus is online

• Available at https://soci424.netlify.app
• Contains schedule, assignments, assessment, and other important information
• Updated with links to slides and lecture recordings, and with any schedule changes regularly

Perusall for online reading/evaluation

• Readings are a central aspect of the course
• All readings will be done through the online tool Perusall
• To register for this class's Perusall, see MyCourses

Grading - SOCI 424

• Each reading is automatically scored 0 points or 1 point
  (Perusall may tell you that the maximum score is 3, but that is not the case in this class)
• Lowest two reading scores dropped at the end of the term
• If you did the reading on time, but did not get credit, messame me to fix the score (really)

Grading - SOCI 624

• Readings will be scored hollistically
• You are expected to participate in annotations and online discussoins

Textbook

• Rawlings, Smith, Moody, and McFarland (2023)
• General introduction to network analysis especially suited to social scientists
• Excellent integration of theory and methods
• Explicit treatment of networks and culture
• Fantastic hands-on tutorials:
  https://inarwhal.github.io/NetworkAnalysisR-book/
• First two readings from this book due Tuesday
• (See also Martin 2009)

Working in R

• The R programming language will be a major compnent of this course
• We will use R (and R Markdown) to manage data, run network analyses, create visualizations, and write up results
• The class assumes some familiarity with programming
• Labs assume you have a laptop you can bring to class
  Let me know ASAP if this won't be possible

Learning R

• Very basic introduction (adapted from Data Carpentry)
• Norm Matloff's fasteR
  For getting quickly up to speed
• Rawlings et al.'s (2023) Tutorials
• We will spend next Tuesday getting R installed on your computer and going over some basics