Nicola Perra, Ph.D.
  • Home
  • About Me
  • Research
    • Dynamical Processes on Time-Varying Networks
    • Contagion Models and Adaptive Behavior
    • Epidemics in Structured Populations
    • Global Epidemic and Mobility Model: GLEaM
    • Modeling and Studying Online Social Networks
    • Resilience of Coevolving and Interdependent Networks
    • Centrality Measures on Complex Networks
  • Publications
  • In the Press
  • Softwares and Online Projects
  • Talks
  • Contacts
  • Home
  • About Me
  • Research
    • Dynamical Processes on Time-Varying Networks
    • Contagion Models and Adaptive Behavior
    • Epidemics in Structured Populations
    • Global Epidemic and Mobility Model: GLEaM
    • Modeling and Studying Online Social Networks
    • Resilience of Coevolving and Interdependent Networks
    • Centrality Measures on Complex Networks
  • Publications
  • In the Press
  • Softwares and Online Projects
  • Talks
  • Contacts

Twitter TOP 10, 2019

Here I am highlighting the top 10 papers, for number of engagements, that I shared in 2019 on my twitter account (@net_science). 

1. Sugi, T., Ito, H., Nishimura, M. and Nagai, K.H., 2019. C. elegans collectively forms dynamical networks. Nature communications, 10 (1), p.683.
https://www.nature.com/articles/s41467-019-08537-y

2. Perra, N. and Rocha, L.E., 2019. Modelling opinion dynamics in the age of algorithmic personalisation. Scientific reports, 9 (1), p.7261.
https://www.nature.com/articles/s41598-019-43830-2

3. Saltelli, A., 2019. A short comment on statistical versus mathematical modelling. Nature communications, 10(1), pp.1-3.
https://www.nature.com/articles/s41467-019-11865-8

4. Aleta, A., Meloni, S., Perra, N., Moreno, Y. Explore with caution: mapping the evolution of scientific interest in physics. EPJ Data Sci. 8, 27 (2019) 
https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-019-0205-9

5. Mattsson, C., 2019. Networks of monetary flow at native resolution. arXiv:1910.05596.
https://arxiv.org/abs/1910.05596

6. Venturini, T., Jacomy, M. and Jensen, P., 2019. What do we see when we look at networks. arXiv:1905.02202.
https://arxiv.org/abs/1905.02202

7. Lambiotte, R., Rosvall, M. and Scholtes, I., 2019. From networks to optimal higher-order models of complex systems. Nature physics, 15 (4), pp.313-320.
https://www.nature.com/articles/s41567-019-0459-y

8. Freitas, C.G., Aquino, A.L., Ramos, H.S., Frery, A.C. and Rosso, O.A., 2019. A detailed characterization of complex networks using Information Theory. Scientific reports, 9 (1), pp.1-12.
https://www.nature.com/articles/s41598-019-53167-5

9. Stone, L., Simberloff, D. and Artzy-Randrup, Y., 2019. Network motifs and their origins. PLoS computational biology, 15 (4), p.e1006749.

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006749

10. Avena-Koenigsberger, A., Yan, X., Kolchinsky, A., van den Heuvel, M., Hagmann, P. and Sporns, O., 2019. A spectrum of routing strategies for brain networks. PLoS computational biology, 15 (3), p.e1006833.
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006833


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