NETS 8941 - Literature Review Seminar - Spring 2022
Thursdays: 4:15 – 5:55pm
January 20 – May 5, 2022
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.
There are no tests, assignments are not graded, but there are several weeks throughout the semester devoted to “Good Science, Good Templates” presentations. These are short 10-15 minute student presentations about a paper of your choosing that was written in a way that is especially insightful and inspires your writing today. These could be papers that have a really accessible structure, papers that are written especially clearly, or papers that inspire your current work. These presentations are designed to hone our eye for how to read good papers and ultimately how to write better papers.
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/.
Week 1: Jan. 20
Introductions and expectations
Readings:
Science & complexity - Weaver. (1948).
Complex networks - Amaral & Ottino. (2004).
Week 2: Jan. 27
Complexity, old and new
Readings:
What complexity science is, and why - Holme. (2022).
Emergent evolution & the social - Wheeler. (1926).
Week 3: Feb. 3
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).
Week 4: Feb. 10
Philosophy in/and/of networks
Readings:
Primary reading: Distinguishing topological and causal explanation - Ross. (2021).
Supplemental reading: Cascade versus mechanism: The diversity of causal structure in science - Ross. (2020).
Supplemental reading: Causal Concepts in Biology: How Pathways Differ from Mechanisms and Why It Matters - Ross. (2021).
Guest participant:
Professor Lauren Ross (University of California, Irvine)
Week 5: Feb. 17
Good science, good templates
Student presentations:
Clara Bay: Multiscale, resurgent epidemics in a hierarchical metapopulation model - Watts, Muhamad, Medina, & Dodds. (2005).
Harrison Hartle: Efficient generation of networks with given expected degrees - Miller & Hagberg. (2011).
+additional discussions on self-organized criticality.
Week 6: Feb. 24
The meaning of the measurement
Readings:
Primary reading: Ousiometrics and Telegnomics: The essence of meaning conforms to a two-dimensional powerful-weak and dangerous-safe framework with diverse corpora presenting a safety bias - Dodds, Alshaabi, Fudolig, Zimmerman, Lovato, Beaulieu, Minot, Arnold, Reagan, & Danforth. (2021).
Primary reading: Meaningful measures of human society in the twenty-first century - Lazer, Hargittai, Freelon, González-Bailón, Munger, Ognyanova, & Radford. (2021).
Supplementary reading: Inventing Temperature - Measurement and Scientific Progress: Chapter 5 - Chang. (2004).
Supplementary reading: Allotaxonometry and rank-turbulence divergence: A universal instrument for comparing complex systems - Dodds, Minot, Arnold, Alshaabi, Adams, Dewhurst, Gray, Frank, Reagan, & Danforth. (2020).
Supplementary reading: Computational timeline reconstruction of the stories surrounding Trump: Story turbulence, narrative control, and collective chronopathy - Dodds, Minot, Arnold, Alshaabi, Adams, Reagan, & Danforth. (2021).
Guest participant:
Professor Peter Dodds (University of Vermont)
Week 7: Mar. 3
Hierarchies, holarchies, structure
Readings:
Primary reading: Quantifying randomness in real networks - Orsini, Dankulov, Colomer-de-Simón, Jamakovic, Mahadevan, Vahdat, Bassler, Toroczkai, Boguñá, Caldarelli, Fortunato, & Krioukov. (2015).
Primary reading: Uncovering the overlapping community structure of complex networks in nature and society - Palla, Derényi, Farkas, & Vicsek. (2005).
Supplementary reading: The ground truth about metadata and community detection in networks - Peel, Larremore, & Clauset. (2017).
Week 8: Mar. 10
Adaptation, dynamics, and evolution
Readings:
Primary reading: Natural Selection and the Concept of a Protein Space - Smith. (1970).
Primary reading: A Reflection on 50 Years of John Maynard Smith’s “Protein Space” - Ogbunugafor. (2020).
Primary reading: The effect of a prudent adaptive behaviour on disease transmission - Scarpino, Allard, & Hébert-Dufresne. (2016).
Supplementary reading: Adaptive networks: Coevolution of disease and topology - Marceau, Noël, Hébert-Dufresne, Allard, & Dubé. (2010).
Supplementary reading: Evolution and emergence of infectious diseases in theoretical and real-world networks - Leventhal, Hill, Nowak, & Bonhoeffer. (2015).
Guest participants:
Professor C. Brandon Ogbunugafor (Yale University)
Professor Samuel V. Scarpino (Pandemic Prevention Institute, The Rockefeller Foundation)
Week 9: Mar. 17
SPRING BREAK NO CLASS
Week 10: Mar. 24
Social construction of networks
Readings:
Primary reading: How humans learn and represent networks - Lynn & Bassett. (2020).
Primary reading: Analyzing the structure of argumentative discourse - Cohen. (1987).
Guest participant:
Dr. Sarah Shugars (New York University; Fall 2022: Rutgers University)
Week 11: Mar. 31
Rare and everywhere
Readings:
Primary reading: Rare and everywhere - Holme. (2019).
Primary reading: Scale free networks are rare - Broido & Clauset. (2019)
Primary reading: Scale free networks well done - Voitalov, van der Hoorn, van der Hofstad, Krioukov. (2019).
Week 12: Apr. 7
Communication, influence, power
Readings:
Legislative Communication and Power: Measuring Leadership in the U.S. House of Representatives from Social Media Data - Ebanks, Yan, Alvarez, Das, & Sinclair. (2022).
Guest participant:
Professor Betsy Sinclair (Washington University in St Louis)
Week 13: Apr. 14
First principles, complex systems, boundaries
Readings:
Primary reading: The information theory of individuality - Krakauer et al. (2020).
Primary reading: Biological Networks: The Tinkerer as an Engineer - Alon. (2003).
Primary reading: The Fourth Dimension of Life: Fractal Geometry and Allometric Scaling of Organisms - West et al. (1999).
Supplementary reading: A General Model for the Origin of Allometric Scaling Laws in Biology - West et al. (1997).
Supplementary reading: Self-similarity of complex networks - Song. (2005).
Supplementary reading: Network Motifs: Simple Building Blocks of Complex Networks - Milo et al. (2002).
Supplementary reading: Growth, innovation, scaling, and the pace of life in cities - Bettencourt. (2007).
Guest participant:
Professor Jessica Flack (Santa Fe Institute)
Week 14: Apr. 21
Good science, good templates
student presentations (x3)
Week 15: Apr. 28
Sciences of the artificial
Readings:
Primary reading: The Architecture of Complexity - Simon. (1962).
Supplementary reading: The Sciences of the Artificial: Chapter 1 - Simon. (1968).
Supplementary reading: The Nature of Complexity: Chapter 1 - Arthur. (2009).