NETS 8941 - Literature Review Seminar - Spring 2023

Thursdays: 3:30 – 5:15pm
January 12 – April 27, 2023
177 Huntington, room 207

Summary

This Literature Review Seminar is course designed to introduce Network Science students to a wide range of foundational research in Network Science and Complex Systems, both contemporary and historical. The goal for students is to leave the course with exposure to the ideas, insights, and techniques that were integral in the creation of Network Science as we know it today. It is difficult to commit rigidly to a single syllabus for this course; as such, the schedule is designed to be edited, expanded upon, and reconsidered. The ultimate goal is less about identifying and mastering a small number of important scientific contributions—instead, I hope this class provides a space to learn about the insights behind the ideas, untangling where and how these ideas came about, and what they evolved into.

This course is open to members of the Network Science Institute community. It is modeled after an informal “journal club” that was hosted by Professor Alessandro Vespignani from 2016-2018, when many of us would sit together on Friday afternoons to discuss a paper. This would attract students, postdocs, and even faculty, all sitting together listening to each others' questions and insights as peers. As the instructor, I will aim to guide discussion and bring students' voices and questions into the conversation, while also being willing to explore tangents and balancing our various expertises.

We also will be inviting “guest participants“ to class. These will typically be more senior researchers who select the article(s) to read and participate in the journal club for that week, essentially as a peer—asking questions, bringing up discussion points, adding context, commenting on other students’ ideas, etc. The idea is not necessarily for the students to hear a lecture from the guest participant, but rather to feel what it’s like to sit around the same table and discuss big ideas. The guest participants are asked to choose the week’s reading(s), which can be about their own work, or ideas that are inspiring their current work, or ideas inspired them as a student, research that they think should be required reading for young network scientists, any/all/none of the above, etc.

Coursework, Class Structure, Grading

This is a weekly discussion-based class. As is the case in typical “journal club” settings, there will naturally be some students who are more interested and invested in the week's readings. I hope to assign readings that are broad enough that every student has at least one week where the readings are especially salient. At the same time, I challenge every student to come to class prepared to ask questions and share their thoughts about the week's readings.

From time to time, we may encounter disruptions to in-person class (e.g. snow, pandemic, etc.). If that is the case, we will meet at my Zoom room (link in email). Zoom etiquette: Nobody likes endless, boring zoom meetings. Please do your part to create a space that is welcoming for everyone to contribute, including yourself.

Instructor

My name is Brennan Klein, and I am a postdoctoral researcher at the Network Science Institute at Northeastern, which is also where I received my PhD in 2020. I am broadly interested in foundational questions in Network Science and Complex Systems, from emergence and higher order structure to information theory and agency. My current research looks at how complex systems are able to represent, predict, and intervene on their surroundings across a number of different scales—all in ways that appear to minimize surprising states in the future. I believe that scientists have an obligation towards openness and curiosity, and this commitment often leads me into surprising collaborations on a wide range of topics. If you would like to learn more about my research, you can visit my website http://brennanklein.com/.

Syllabus below (or pdf here).

Week 0: Jan. 12

Week 1: Jan. 19

Complexity, old and new

Readings:

• Primary reading: Emergent evolution & the social - Wheeler. (1926).

• Primary reading: The architecture of complexity - Simon. (1962).

• Primary reading: What complexity science is, and why - Holme. (2022).

  • Supplementary reading: Science & complexity - Weaver. (1948).

  • Supplementary reading: Complex networks - Amaral & Ottino. (2004).

  • Supplementary reading: Principles of the self-organizing system - Ashby. (1962).

Week 2: Jan. 26

Criticality, chaos, and… networks?

Readings:

• Primary reading: Self-organized criticality: An explanation of 1/f noise - Bak, Tang, & Wiesenfeld. (1987).

  • Supplementary reading: Self-organized criticality - Bak, Tang, & Wiesenfeld. (1988).

  • Supplementary reading: More is different - Anderson. (1972).

  • Supplementary reading: What is complexity? - Gell-mann. (1995).

Guest participant:

• Professor Alessandro Vespignani (Northeastern University)

Additional resources:

• SocSim Python package: BTW model - https://socsim.readthedocs.io/en/latest/BTW.html

  • Manna Model - toppling two grains of sand, but with stochasticity

• How self-organized criticality works: A unified mean-field picture - Vespignani & Zapperi. (1998).

• True scale-free networks hidden by finite size effects - Serafino, Cimini, Maritan, Rinaldo, Suweis, Banavar, & Caldarelli. (2021).

• (From Moritz Laber) 25 Years of Self-organized Criticality: Concepts and Controversies - Watkins et al. (2015).

Week 3: Feb. 2

What is a network and why?

Readings:

• Primary reading: Statistical inference links data and theory in network science. Peel, Peixoto, De Domenico. (2022).

• Primary reading: When is a network a network? Multi-order graphical model selection in pathways and temporal networks. Scholtes. (2017).

  • Supplementary reading: On the nature of explanations offered by network science: A perspective from and for practicing neuroscientists. Bertolero & Bassett. (2020).

  • Supplementary reading: The role of models in science. Rosenblueth & Wiener. (1945).