Mikko Kivelä

6.4k total citations · 2 hit papers
50 papers, 4.0k citations indexed

About

Mikko Kivelä is a scholar working on Statistical and Nonlinear Physics, Transportation and Experimental and Cognitive Psychology. According to data from OpenAlex, Mikko Kivelä has authored 50 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Statistical and Nonlinear Physics, 8 papers in Transportation and 7 papers in Experimental and Cognitive Psychology. Recurrent topics in Mikko Kivelä's work include Complex Network Analysis Techniques (34 papers), Opinion Dynamics and Social Influence (32 papers) and Human Mobility and Location-Based Analysis (8 papers). Mikko Kivelä is often cited by papers focused on Complex Network Analysis Techniques (34 papers), Opinion Dynamics and Social Influence (32 papers) and Human Mobility and Location-Based Analysis (8 papers). Mikko Kivelä collaborates with scholars based in Finland, United Kingdom and France. Mikko Kivelä's co-authors include Mason A. Porter, Àlex Arenas, Yamir Moreno, James P. Gleeson, Marc Barthélemy, Jari Saramäki, Kimmo Kaski, János Kertész, Jukka‐Pekka Onnela and Márton Karsai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Mikko Kivelä

48 papers receiving 3.9k citations

Hit Papers

Multilayer networks 2011 2026 2016 2021 2014 2011 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mikko Kivelä Finland 19 2.4k 667 574 465 430 50 4.0k
James P. Gleeson Ireland 31 3.1k 1.3× 806 1.2× 768 1.3× 435 0.9× 508 1.2× 116 5.5k
Manlio De Domenico Italy 32 2.3k 1.0× 615 0.9× 928 1.6× 655 1.4× 614 1.4× 111 5.0k
Lazaros K. Gallos United States 21 3.0k 1.2× 608 0.9× 416 0.7× 349 0.8× 573 1.3× 57 4.3k
M. Ángeles Serrano Spain 29 2.7k 1.1× 438 0.7× 417 0.7× 345 0.7× 568 1.3× 69 4.2k
Vincenzo Nicosia United Kingdom 25 1.7k 0.7× 732 1.1× 321 0.6× 327 0.7× 433 1.0× 67 3.4k
Sune Lehmann Denmark 32 2.0k 0.8× 494 0.7× 855 1.5× 654 1.4× 454 1.1× 102 4.8k
Francisco A. Rodrigues Brazil 28 2.2k 0.9× 1.2k 1.9× 416 0.7× 587 1.3× 561 1.3× 131 5.0k
Beom Jun Kim South Korea 29 3.0k 1.3× 1.4k 2.1× 684 1.2× 321 0.7× 440 1.0× 160 5.2k
Mark Newman United Kingdom 21 2.9k 1.2× 1.0k 1.5× 851 1.5× 787 1.7× 770 1.8× 71 7.1k
Zengru Di China 28 1.7k 0.7× 612 0.9× 262 0.5× 382 0.8× 542 1.3× 173 3.3k

Countries citing papers authored by Mikko Kivelä

Since Specialization
Citations

This map shows the geographic impact of Mikko Kivelä's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mikko Kivelä with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikko Kivelä more than expected).

Fields of papers citing papers by Mikko Kivelä

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mikko Kivelä. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mikko Kivelä. The network helps show where Mikko Kivelä may publish in the future.

Co-authorship network of co-authors of Mikko Kivelä

This figure shows the co-authorship network connecting the top 25 collaborators of Mikko Kivelä. A scholar is included among the top collaborators of Mikko Kivelä based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mikko Kivelä. Mikko Kivelä is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kivelä, Mikko, et al.. (2025). Strength and weakness of disease-induced herd immunity in networks. Proceedings of the National Academy of Sciences. 122(28). e2421460122–e2421460122. 1 indexed citations
2.
Stegehuis, Clara, et al.. (2025). Homophily within and across groups. Nature Communications. 16(1). 11351–11351. 1 indexed citations
3.
Gleeson, James P., et al.. (2024). Effectiveness of contact tracing on networks with cliques. Physical review. E. 109(2). 24303–24303. 3 indexed citations
4.
Kivelä, Mikko, et al.. (2024). pymnet: A Python Library for MultilayerNetworks. The Journal of Open Source Software. 9(99). 6930–6930. 1 indexed citations
5.
Kanniainen, Juho, et al.. (2023). Investor trade allocation patterns in stock markets. Journal of Economic Behavior & Organization. 210. 191–209.
6.
Kivelä, Mikko, et al.. (2023). Reticula: A temporal network and hypergraph analysis software package. SoftwareX. 21. 101301–101301. 6 indexed citations
7.
Karsai, Márton, et al.. (2022). Directed percolation in temporal networks. Physical Review Research. 4(2). 8 indexed citations
8.
Karsai, Márton, et al.. (2022). Directed percolation in random temporal network models with heterogeneities. Physical review. E. 105(5). 54313–54313. 7 indexed citations
9.
Kivelä, Mikko, et al.. (2022). Herd immunity and epidemic size in networks with vaccination homophily. Physical review. E. 105(5). L052301–L052301. 24 indexed citations
10.
Gauvin, Laëtitia, Mathieu Génois, Márton Karsai, et al.. (2022). Randomized Reference Models for Temporal Networks. SIAM Review. 64(4). 763–830. 32 indexed citations
11.
Kivelä, Mikko, et al.. (2022). Epidemic spreading and digital contact tracing: Effects of heterogeneous mixing and quarantine failures. Physical review. E. 105(4). 44313–44313. 13 indexed citations
12.
Barrat, Alain, Ciro Cattuto, Mikko Kivelä, Sune Lehmann, & Jari Saramäki. (2021). Effect of manual and digital contact tracing on COVID-19 outbreaks: a study on empirical contact data. Journal of The Royal Society Interface. 18(178). 59 indexed citations
13.
Karsai, Márton, et al.. (2021). Source code and for "Directed Percolation in Temporal Networks" and "Directed Percolation in Random Temporal Network Models with Heterogeneities". Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
14.
Karsai, Márton, et al.. (2020). Efficient limited-time reachability estimation in temporal networks. Physical review. E. 101(5). 52303–52303. 14 indexed citations
15.
Kivelä, Mikko, et al.. (2017). Mapping temporal-network percolation to weighted, static event graphs. arXiv (Cornell University). 23 indexed citations
16.
Cozzo, Emanuele, Mikko Kivelä, Manlio De Domenico, et al.. (2013). Clustering Coefficients in Multiplex Networks.. arXiv (Cornell University). 14 indexed citations
17.
Toivonen, Riitta, et al.. (2012). Networks of Emotion Concepts. PLoS ONE. 7(1). e28883–e28883. 33 indexed citations
18.
Lancichinetti, Andrea, Mikko Kivelä, Jari Saramäki, & Santo Fortunato. (2010). Characterizing the Community Structure of Complex Networks. PLoS ONE. 5(8). e11976–e11976. 173 indexed citations
19.
Toivonen, Riitta, Lauri Kovanen, Mikko Kivelä, et al.. (2008). A comparative study of stochastic algorithmic models for social networks. arXiv (Cornell University). 1 indexed citations
20.
Saramäki, Jari, Mikko Kivelä, Jukka‐Pekka Onnela, Kimmo Kaski, & János Kertész. (2007). Generalizations of the clustering coefficient to weighted complex networks. Physical Review E. 75(2). 27105–27105. 461 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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