FASS 210 - Language Network Science

Put power into your words

Our lives are richly intertwined with networks: from social networks, to the Internet, to the micro-structure of our brains. Though programming exercises, students will learn the science behind networks and apply them to problems in modern linguistics, including language networks of bilingual Canadians, language learning, and the network structure of the mental lexicon.

FASS 210 runs May 11 - June 8, 2023. Complete before the workload of your other classes kick in!

Register now. Space is limited.

Summer 2023 course outline →

What you will learn and when it is offered

What you'll learn

  1. Develop skills for analyzing networks.
  2. Gain experience programming with large data sets.
  3. Reflect on network structure and use it to gain insight into networks, including language networksand social networks.
  4. Apply the insights about language networks to human health.


  • Programming platform (free software): Google Collaborary or your preferred Python programming environment. No math or programming experience is required.
  • Students will need to bring a laptop to class. The SFU library loans laptops for student use.
  • Required textbook: Menczer, Filippo, Santo Fortunato and Clayton A. Davis. (2020) A First Course in Network Science. Cambridge University Press.

When it is offered

Location: Burnaby Campus


  • May 11
  • May 18
  • May 25
  • June 1
  • June 8


  • 9:30 am - 12:20 pm

Course instructor

John Alderete

John Alderete is a professor of Linguistics and Cognitive Science. His work investigates the mental life of speaking, listening, and learning. He combines computational modeling, insights from linguistics and psychology, and Big Data from the world’s languages to probe the nature of how language is used by humans. He is excited to teach this course on network science because recent research has shown that language can be viewed as a rich interconnected network of linguistic units, and understanding the basic abilities of speaking and listening is informed greatly by probing these language networks. In taking this class, students will learn practical skills in analyzing networks, and they will use these skills to understand how language is investigated in modern linguistics and other allied disciplines, like psychology, health sciences, and computer science.

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