NETS 8941 - Literature Review Seminar - Spring 2026

Thursdays: 3:30 – 5:15pm
January 8 – April 23, 2026
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 not about identifying and mastering a small number of important scientific contributions—instead, this class provides a space to learn about the insights behind the ideas we use today, 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 NetSI members would sit together on Friday afternoons to discuss a paper. This would attract students, postdocs, and 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 and will likely participate more. 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, no matter the topic.

Instructor

Brennan Klein is core faculty at the Network Science Institute and Assistant Teaching Professor in the Department of Physics. He is the program director of the MS in Complex Network Analysis at Northeastern University. Prof. Klein is also the director of the Complexity & Society Lab, which is focused on two broad research areas: 1) Information, emergence, and inference in complex systems: developing tools and theory for characterizing dynamics, structure, and scale in networks, and 2) Public health and public safety: drawing on complex systems science to document—and fight against—emergent or systemic disparities in society, especially as they relate to public health and public safety. As of 2025, he is also the director of NetSI Sport, an interdisciplinary research group focusing on complex systems-inspired approaches to sports analytics. In 2023, Prof. Klein was awarded the René Thom Young Researcher Award, given to a researcher to recognize substantial early career contributions and leadership in research in Complex Systems-related fields. Prof. Klein is the Data for Justice Fellow at the Institute on Policing, Incarceration & Public Safety at Harvard University’s Hutchins Center for African & African American Research. He received a PhD in Network Science in 2020 from Northeastern University and earned his BA in Cognitive Science & Psychology from Swarthmore College in 2014. Website: brennanklein.com.

Syllabus below (or pdf here).

Week 1: Jan. 8

Introduction to the course and semester goals

Pre-class homework:

  • Please come to class with the following:

    • A list of your favorite papers (between 1 and 5, nothing too substantial) about networks or complex systems. Don't think too much about this! Just be ready to discuss in class.

    • A list of possible scholars who you think would be good guests to invite to the course (either this year, or for future iterations).

Week 2: Jan. 15

Complexity, old and new

Readings:

  • Primary reading: Wheeler, W.M., (1926). Emergent Evolution and the Social. Science, 64(1662), pp. 433-440. doi: https://www.jstor.org/stable/1651238.

  • Primary reading: Simon, H. A. (1962). The Architecture of Complexity. Proceedings of the American Philosophical Society, 106(6), 467–482. doi: http://www.jstor.org/stable/985254.

  • Primary reading: Holme, P. (2022). What complexity science is, and why. arXiv: 2201.03762.

    • Supplementary reading: Weaver, W. (1948). Science and Complexity. American Scientist, 36(4), 536–544. doi: http://www.jstor.org/stable/27826254.

    • Supplementary reading: Amaral, L.A.N., Ottino, J.M. (2004). Complex networks. European Physical Journal B 38, 147–162. doi: 10.1140/epjb/e2004-00110-5.

    • Supplementary reading: Ashby, W.R. (1962). Principles of the self-organizing system. In Principles of Self-Organization: Transactions of the University of Illinois Symposium, H. Von Foerster and G.W. Zopf, Jr. (eds.), Pergamon Press: London, UK, pp. 255-278.

Week 3: Jan. 22

Philosophy in/and/of networks

Readings:

  • Primary reading: Ross, L.N. (2021). Distinguishing topological and causal explanation. Synthese, 198, 9803-9820. doi: 10.1007/s11229-020-02685-1.

    • Supplementary reading: Bertolero, M. & Bassett., D.S. (2020). On the nature of explanations offered by network science: A perspective from and for practicing neuroscientists. Topics in Cognitive Science, 12, 1272–1293. doi: 10.1111/tops.12504.

    • Supplementary reading: Ross, L.N. (2022). Cascade versus mechanism: The diversity of causal structure in science. The British Journal for the Philosophy of Science, 1. doi: 10.1086/723623.

    • Supplementary reading: Ross, L.N. (2021). Causal Concepts in Biology: How Pathways Differ from Mechanisms and Why It Matters. The British Journal for the Philosophy of Science, 72(1), 131-158. doi: 10.1093/bjps/axy078.

    • Supplementary reading: Chang, H. (2004). Inventing temperature: Measurement and scientific progress: Chapter 5. Oxford University Press.

    • Supplementary reading: Andersen, H. (2014). A field guide to mechanisms: Part I. Philosophy Compass, 9(4), 274-283. doi: 10.1111/phc3.12119.

    • Supplementary reading: Andersen, H. (2014). A field guide to mechanisms: Part II. Philosophy Compass, 9(4), 284-293. doi: 10.1111/phc3.12118.

    • Supplementary reading: Rosenblueth, A. & Wiener, N. (1945). The role of models in science. Philosophy of Science, 12(4), 316-321. doi: 10.1086/286874.

Additional resources:

  • Ross, L.N. & Bassett, D.S. (2024). Causation in neuroscience: keeping mechanism meaningful. Nature Reviews Neuroscience. doi: 10.1038/s41583-023-00778-7.

Week 4: Jan. 29

Topic TBD

Readings:

  • Primary reading: TBD

    • Supplementary reading: TBD

Additional resources:

  • TBD

Week 5: Feb. 5

Criticality, chaos, and networks (w/ Alessandro Vespignani)

Readings:

  • Primary reading: Bak, P., & Chen, K. (1991). Self-organized criticality. Scientific American, 264(1), 46-53. url: http://www.jstor.org/stable/24936753.

  • Primary reading: Bak, P., Tang, C., & Wiesenfeld, K. (1988). Self-organized criticality. Physical Review A, 38(1), 364. doi: 10.1103/PhysRevA.38.364.

    • Supplementary reading: Vespignani, A. & Zapperi, S. (1998). How self-organized criticality works: A unified mean-field picture. Physical Review E, 57(6), 6345. doi: 10.1103/PhysRevE.57.6345.

    • Supplementary reading: Dickman, R., Vespignani, A., & Zapperi, S. (1998). Self-organized criticality as an absorbing-state phase transition. Physical Review E, 57(5), 5095. doi: 10.1103/PhysRevE.57.5095.

    • Supplementary reading: Bak, P., Tang, C., & Wiesenfeld, K. (1987). Self-organized criticality: An explanation of the 1/f noise. Physical Review Letters, 59(4), 381. doi: 10.1103/PhysRevLett.59.381.

    • Supplementary reading: Anderson, P. W. (1972). More Is Different: Broken symmetry and the nature of the hierarchical structure of science. Science, 177(4047), 393-396. doi: 10.1126/science.177.4047.393.

    • Supplementary reading: Gell-Mann (1995). What is Complexity? Complexity, 1(1). John Wiley and Sons, Inc.

Guest participant:

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

  • Serafino, M., Cimini, G., Maritan, A., Rinaldo, A., Suweis, S., Banavar, J. R., & Caldarelli, G. (2021). True scale-free networks hidden by finite size effects. Proceedings of the National Academy of Sciences, 118(2), e2013825118. doi: 10.1073/pnas.2013825118.

  • Watkins, N.W., Pruessner, G., Chapman, S.C. et al. (2016). 25 Years of Self-organized Criticality: Concepts and Controversies. Space Science Review 198, 3–44. doi: 10.1007/s11214-015-0155-x.

Week 6: Feb. 12

Statistics, description, and inference in complex networks

Readings:

  • Primary reading: Peel, L., Peixoto, T.P. & De Domenico, M. (2022). Statistical inference links data and theory in network science. Nature Communications, 13, 6794. doi: 10.1038/s41467-022-34267-9.

  • Primary reading: Peixoto T.P. (2023). Descriptive vs. Inferential Community Detection in Networks: Pitfalls, Myths and Half-Truths. Cambridge: Cambridge University Press. doi: 10.1017/9781009118897.

    • Supplementary reading: Peixoto, T.P. (2023 ed.). Bayesian stochastic blockmodeling. arXiv: 1705.10225 v9. [also published under Peixoto, T.P. (2019). Bayesian Stochastic Blockmodeling. In Advances in Network Clustering and Blockmodeling (eds P. Doreian, V. Batagelj and A. Ferligoj). doi: 10.1002/9781119483298.ch11.]

    • Supplementary reading: Peixoto, T.P. (2019). Network reconstruction and community detection from dynamics. Physical Review Letters, 123(12), 128301. doi: 10.1103/PhysRevLett.123.128301.

    • Supplementary reading: Peixoto, T.P. (2024). Scalable network reconstruction in subquadratic time. arXiv: 2401.01404.

Additional resources:

Week 7: Feb. 19

Network motifs and structure

Readings:

  • Primary reading: Orsini, C., Dankulov, M., Colomer-de-Simón, P., Jamakovic, A., Mahadevan, P., Vahdat, A., Bassler, K., Toroczkai, Z., Boguñá, M., Caldarelli, G., Fortunato, S. & Krioukov, D. (2015). Quantifying randomness in real networks. Nature Communications, 6, 8627. doi: 10.1038/ncomms9627.

  • Primary reading: Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002). Network motifs: simple building blocks of complex networks. Science, 298(5594), 824-827. doi: 10.1126/science.298.5594.824.

  • Primary reading: Stamm, F. I., Scholkemper, M., Strohmaier, M., & Schaub, M. T. (2023). Neighborhood structure configuration models. In Proceedings of the ACM Web Conference 2023 (pp. 210-220). doi: 10.1145/3543507.3583266.

    • Supplementary reading: Hočevar, T. & Demšar, J. (2014). A combinatorial approach to graphlet counting. Bioinformatics, 30(4), 559–565. doi: 10.1093/bioinformatics/btt717.

    • Supplementary reading: Karrer, B. & Newman, M. E. (2010). Random graphs containing arbitrary distributions of subgraphs. Physical Review E, 82(6), 066118. doi: 10.1103/PhysRevE.82.066118.

    • Supplementary reading: Stegehuis, C., Hofstad, R.v.d. & van Leeuwaarden, J.S.H. (2019). Variational principle for scale-free network motifs. Scientific Reports, 9, 6762. doi: 10.1038/s41598-019-43050-8.

    • Supplementary reading: Ribeiro, P., Paredes, P., Silva, M. E., Aparicio, D., & Silva, F. (2021). A survey on subgraph counting: Concepts, algorithms, and applications to network motifs and graphlets. ACM Computing Surveys (CSUR), 54(2), 1-36. doi: 10.1145/3433652.

Additional resources:

  • Mahadevan, P., Krioukov, D., Fall, K., & Vahdat, A. (2006). Systematic topology analysis and generation using degree correlations. ACM SIGCOMM Computer Communication Review, 36(4), 135-146. doi: 10.1145/1151659.1159930.

Week 8: Feb. 26

Thinking and representing as network scientists (w/ Tina Eliassi-Rad)

Readings:

  • Primary reading: Asimov, I. (1958). The feeling of power. The Magazine of Fantasy and Science Fiction. https://hex.ooo/library/power.html

    • Supplementary reading: Torres, L., Blevins, A. S., Bassett, D., & Eliassi-Rad, T. (2021). The why, how, and when of representations for complex systems. SIAM Review, 63(3), 435-485. doi: 10.1137/20M1355896.

Guest participant:

Additional resources:

  • Dechter, R. & Pearl, J. (1985). Generalized best-first search strategies and the optimality of A*. Journal of the ACM (JACM), 32(3), 505-536. doi: 10.1145/3828.3830.

Week 9: Mar. 5

SPRING BREAK NO CLASS

Week 10: Mar. 12

Topic TBD (w/ David Krakauer)

Readings:

  • Primary reading: TBD

    • Supplementary reading: TBD

Guest participant:

Additional resources:

  • TBD

Week 11: Mar. 19

Topic TBD

Readings:

  • Primary reading: TBD

    • Supplementary reading: TBD

Guest participant:

  • TBD

Additional resources:

  • TBD

Week 12: Mar. 26

Topic TBD

Readings:

  • Primary reading: TBD

    • Supplementary reading: TBD

Guest participant:

  • TBD

Additional resources:

  • TBD

Week 13: Apr. 2

Topic TBD

Readings:

  • Primary reading: TBD

    • Supplementary reading: TBD

Guest participant:

  • TBD

Additional resources:

  • TBD

Week 14: Apr. 9

Topic TBD

Readings:

  • Primary reading: TBD

    • Supplementary reading: TBD

Guest participant:

  • TBD

Additional resources:

  • TBD

Week 15: Apr. 16

Topic TBD

Readings:

  • Primary reading: TBD

    • Supplementary reading: TBD

Guest participant:

  • TBD

Additional resources:

  • TBD

Week 16: Apr. 23

Topic TBD (w/ Raissa D’Souza)

Readings:

  • Primary reading: TBD

    • Supplementary reading: TBD

Guest participant:

Additional resources:

  • TBD