title: "NetSI Journal Club" author:

• name: Network Science Institute ...

Organizer: Stefan McCabe

Time: Every other Friday, 2:00--3:00

Candidate Papers: Link

• Zhao, Kino. Forthcoming. “Sample Representation in the Social Sciences.” Synthese. https://doi.org/10.1007/s11229-020-02621-3.

• Schaub, Michael T., and Leto Peel. 2020. “Hierarchical Community Structure in Networks.” arXiv:2009.07196 [cs.SI]. http://arxiv.org/abs/2009.07196.
• Peel, Leto, and Michael T. Schaub. 2020. “Detectability of Hierarchical Communities in Networks.” arXiv:2009.07525 [cs.SI]. http://arxiv.org/abs/2009.07525.

• Jacomy, Mathieu. 2020. “Epistemic Clashes in Network Science: Mapping the Tensions between Idiographic and Nomothetic Subcultures.” Big Data & Society 7 (2). https://doi.org/10.1177/2053951720949577.

Organizer: Stefan McCabe

Time: Every other Thursday, 2:00--3:00

• Aktas, Mehmet E., Esra Akbas, and Ahmed El Fatmaoui. 2019. “Persistence Homology of Networks: Methods and Applications.” Applied Network Science 4 (1): 61. https://doi.org/10.1007/s41109-019-0179-3.

• Wu, Xin-Zeng, Allon G. Percus, Keith Burghardt, and Kristina Lerman. 2019. “The Transsortative Structure of Networks.” arXiv:1910.09538 [physics.soc-ph]. http://arxiv.org/abs/1910.09538.
• Altenburger, Kristen M., and Johan Ugander. 2018. “Monophily in Social Networks Introduces Similarity Among Friends-of-Friends.” Nature Human Behaviour 2 (4): 284–90. https://doi.org/10.1038/s41562-018-0321-8. (optional)

• Rodrigues, Francisco A., Thomas Peron, Colm Connaughton, Jurgen Kurths, and Yamir Moreno. 2019. “A Machine Learning Approach to Predicting Dynamical Observables from Network Structure.” arXiv:1910.00544 [physics.soc-ph]. http://arxiv.org/abs/1910.00544.

• Asllani, Malbor, Renaud Lambiotte, and Timoteo Carletti. 2018. “Structure and Dynamical Behavior of Non-Normal Networks.” Science Advances 4 (12): eaau9403. https://doi.org/10.1126/sciadv.aau9403.

• Cantwell, George T., and M. E. J. Newman. 2019. “Message Passing on Networks with Loops.” arXiv:1907.08252 [cs.SI]. http://arxiv.org/abs/1907.08252.

Organizer: Stefan McCabe

Time: Every other Friday, 3:00--4:00

• Gerlach, Martin, and Eduardo G. Altmann. 2019. “Testing Statistical Laws in Complex Systems.” Physical Review Letters 122 (16): 168301. https://doi.org/10.1103/PhysRevLett.122.168301.

• Munger, Kevin. 2019. “Knowledge Decays: Temporal Validity in Online Social Science.” Working Paper. https://osf.io/bka9z/.

Organizer: Stefan McCabe

Time: Every other Friday, 3:00--4:00.

• Canright, Geoffrey S., and Kenth Engø-Monsen. 2005. “Epidemic Spreading Over Networks – A View from Neighbourhoods.” Telektronikk 101 (1): 65–85.
• Martin, Travis, Xiao Zhang, and M. E. J. Newman. 2014. “Localization and Centrality in Networks.” Physical Review E 90 (5): 052808. https://doi.org/10.1103/PhysRevE.90.052808.
• Kitsak, Maksim, Lazaros K. Gallos, Shlomo Havlin, Fredrik Liljeros, Lev Muchnik, H. Eugene Stanley, and Hernán A. Makse. 2010. “Identification of Influential Spreaders in Complex Networks.” Nature Physics 6 (11): 888–93. https://doi.org/10.1038/nphys1746.

• Canright, Geoffrey S., and Kenth Engø-Monsen. 2005. “Epidemic Spreading Over Networks – A View from Neighbourhoods.” Telektronikk 101 (1): 65–85.
• Fortunato, Santo. 2010. “Community Detection in Graphs.” Physics Reports 486 (3–5): 75–174. https://doi.org/10.1016/j.physrep.2009.11.002.

• Eckles, Dean, Elchanan Mossel, M. Amin Rahimian, and Subhabrata Sen. 2018. “Long Ties Accelerate Noisy Threshold-Based Contagions.” arXiv:1810.03579v2 [cs.SI]. http://arxiv.org/abs/1810.03579v2.
• Juul, Jonas S., and Mason A. Porter. 2019. “Hipsters on Networks: How a Minority Group of Individuals Can Lead to an Antiestablishment Majority.” Physical Review E 99 (2). https://doi.org/10.1103/PhysRevE.99.022313.

(with Austin Benson)

Note: this session will meet 3:30--4:30 to accommodate Thomas Malone's talk at NetSI.

• Overgoor, Jan, Austin R. Benson, and Johan Ugander. 2018. “Choosing to Grow a Graph: Modeling Network Formation as Discrete Choice.” arXiv:1811.05008 [cs.SI]. http://arxiv.org/abs/1811.05008.

• De Domenico, Manlio, and Jacob Biamonte. 2016. “Spectral Entropies as Information-Theoretic Tools for Complex Network Comparison.” Physical Review X 6 (4). https://doi.org/10.1103/PhysRevX.6.041062.
• Masuda, Naoki, and Petter Holme. 2019. “Detecting Sequences of System States in Temporal Networks.” Scientific Reports 9 (1). https://doi.org/10.1038/s41598-018-37534-2.

Organizer: Ryan J. Gallagher

(with NETS 8941)

• Voitalov, Ivan, Pim van der Hoorn, Remco van der Hofstad, and Dmitri Krioukov. 2018. “Scale-Free Networks Well Done.” arXiv:1811.02071 [physics.soc-ph]. http://arxiv.org/abs/1811.02071.

• Chaney, Allison J. B., Brandon M. Stewart, and Barbara E. Engelhardt. 2018. “How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility.” In Proceedings of the 12th ACM Conference on Recommender Systems, 224–32. New York: ACM Press. https://doi.org/10.1145/3240323.3240370.
• Healy, Kieran. 2015. “The Performativity of Networks.” European Journal of Sociology 56 (2): 175–205. https://doi.org/10.1017/S0003975615000107.

(Part 2, with Emergent Epidemics Lab)

• Young, Jean-Gabriel, Guillaume St-Onge, Patrick Desrosiers, and Louis J. Dubé. 2018. “Universality of the Stochastic Block Model.” Physical Review E 98 (3). https://doi.org/10.1103/PhysRevE.98.032309.

(Part 1, with Emergent Epidemics Lab)

• Hoffmann, Till, Leto Peel, Renaud Lambiotte, and Nick S. Jones. 2018. “Community Detection in Networks with Unobserved Edges.” arXiv:1808.06079 [physics.soc-ph]. http://arxiv.org/abs/1808.06079.

• Newman, Mark E. J. 2018. “Network Structure from Rich but Noisy Data.” Nature Physics 14 (6): 542–45. https://doi.org/10.1038/s41567-018-0076-1.
• Young, Jean-Gabriel, Laurent Hébert-Dufresne, Edward Laurence, Charles Murphy, Guillaume St-Onge, and Patrick Desrosiers. 2018. “Network Archaeology: Phase Transition in the Recoverability of Network History.” arXiv:1803.09191 [physics.soc-ph]. http://arxiv.org/abs/1803.09191.

Organizer: Ryan J. Gallagher

• Bagrow, James P., and Erik M. Bollt. 2018. “An Information-Theoretic, All-Scales Approach to Comparing Networks.” arXiv:1804.03665 [cs.SI]. http://arxiv.org/abs/1804.03665.
• Hébert-Dufresne, Laurent, Joshua A. Grochow, and Antoine Allard. 2016. “Multi-Scale Structure and Topological Anomaly Detection via a New Network Statistic: The Onion Decomposition.” Scientific Reports 6 (1). https://doi.org/10.1038/srep31708.

• Altenburger, Kristen M., and Johan Ugander. 2018. “Monophily in Social Networks Introduces Similarity Among Friends-of-Friends.” Nature Human Behaviour 2 (4): 284–90. https://doi.org/10.1038/s41562-018-0321-8.
• Peel, Leto, Jean-Charles Delvenne, and Renaud Lambiotte. 2018. “Multiscale Mixing Patterns in Networks.” Proceedings of the National Academy of Sciences 115 (16): 4057–62. https://doi.org/10.1073/pnas.1713019115.

Organizer: Ryan J. Gallagher

• Goel, Sharad, Ashton Anderson, Jake Hofman, and Duncan J. Watts. 2015. “The Structural Virality of Online Diffusion.” Management Science 62 (1), 180–96. https://doi.org/10.1287/mnsc.2015.2158.

• Broido, Anna D., and Aaron Clauset. 2018. “Scale-Free Networks Are Rare.” arXiv:1801.03400 [physics.soc-ph]. http://arxiv.org/abs/1801.03400.