Michele Starnini

3.9k total citations · 2 hit papers
43 papers, 2.1k citations indexed

About

Michele Starnini is a scholar working on Statistical and Nonlinear Physics, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Michele Starnini has authored 43 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Statistical and Nonlinear Physics, 19 papers in Sociology and Political Science and 10 papers in Artificial Intelligence. Recurrent topics in Michele Starnini's work include Complex Network Analysis Techniques (24 papers), Opinion Dynamics and Social Influence (23 papers) and Misinformation and Its Impacts (13 papers). Michele Starnini is often cited by papers focused on Complex Network Analysis Techniques (24 papers), Opinion Dynamics and Social Influence (23 papers) and Misinformation and Its Impacts (13 papers). Michele Starnini collaborates with scholars based in Spain, Italy and United States. Michele Starnini's co-authors include Gianmarco De Francisci Morales, Matteo Cinelli, Walter Quattrociocchi, Alessandro Galeazzi, Romualdo Pastor‐Satorras, Igor M. Sokolov, Philipp Lorenz-Spreen, Fabian Baumann, Andrea Baronchelli and Daniela Paolotti and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and SHILAP Revista de lepidopterología.

In The Last Decade

Michele Starnini

39 papers receiving 2.0k citations

Hit Papers

The echo chamber effect on social media 2020 2026 2022 2024 2021 2020 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michele Starnini Spain 19 1.0k 1.0k 565 320 137 43 2.1k
Robert M. Bond United States 13 1.3k 1.3× 632 0.6× 950 1.7× 311 1.0× 69 0.5× 45 2.5k
Dean Eckles United States 23 1.4k 1.4× 371 0.4× 561 1.0× 502 1.6× 139 1.0× 47 2.4k
Jason Kaufman United States 20 1.4k 1.4× 401 0.4× 495 0.9× 138 0.4× 77 0.6× 55 2.4k
Matteo Cinelli Italy 16 1.0k 1.0× 427 0.4× 518 0.9× 351 1.1× 416 3.0× 60 2.3k
Gueorgi Kossinets United States 9 978 0.9× 1.3k 1.3× 413 0.7× 440 1.4× 29 0.2× 12 2.9k
Jaime E. Settle United States 17 1.5k 1.5× 659 0.7× 1.0k 1.8× 307 1.0× 30 0.2× 32 2.7k
D. Walker United States 11 957 0.9× 820 0.8× 338 0.6× 215 0.7× 26 0.2× 31 2.0k
Michela Del Vicario Italy 13 2.2k 2.1× 1.0k 1.0× 1.2k 2.1× 657 2.1× 31 0.2× 15 3.0k
Jürgen Lerner Germany 17 369 0.4× 431 0.4× 196 0.3× 216 0.7× 74 0.5× 42 1.1k
Alessandro Galeazzi Italy 11 992 1.0× 319 0.3× 530 0.9× 287 0.9× 396 2.9× 24 2.1k

Countries citing papers authored by Michele Starnini

Since Specialization
Citations

This map shows the geographic impact of Michele Starnini'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 Michele Starnini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michele Starnini more than expected).

Fields of papers citing papers by Michele Starnini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michele Starnini. 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 Michele Starnini. The network helps show where Michele Starnini may publish in the future.

Co-authorship network of co-authors of Michele Starnini

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Starnini. A scholar is included among the top collaborators of Michele Starnini 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 Michele Starnini. Michele Starnini 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.
Bisin, Alberto, et al.. (2025). Modeling adaptive forward-looking behavior in epidemics on networks. Journal of Economic Behavior & Organization. 232. 106914–106914. 1 indexed citations
3.
Starnini, Michele, et al.. (2025). Social network heterogeneity promotes depolarization of multidimensional correlated opinions. Physical Review Research. 7(1).
4.
Starnini, Michele, et al.. (2024). Charting mobility patterns in the scientific knowledge landscape. EPJ Data Science. 13(1). 4 indexed citations
6.
Perotti, Alan, et al.. (2023). Machine Learning Model as a Useful Tool for Prediction of Thyroid Nodules Histology, Aggressiveness and Treatment-Related Complications. Journal of Personalized Medicine. 13(11). 1615–1615. 1 indexed citations
7.
Monti, Corrado, et al.. (2023). Evidence of Demographic rather than Ideological Segregation in News Discussion on Reddit. arXiv (Cornell University). 2777–2786. 10 indexed citations
8.
Monti, Corrado, Matteo Cinelli, Carlo Michele Valensise, Walter Quattrociocchi, & Michele Starnini. (2023). Online conspiracy communities are more resilient to deplatforming. PNAS Nexus. 2(10). pgad324–pgad324. 9 indexed citations
9.
Mejova, Yelena, Kyriaki Kalimeri, André Panisson, et al.. (2023). Global Misinformation Spillovers in the Vaccination Debate Before and During the COVID-19 Pandemic: Multilingual Twitter Study. SHILAP Revista de lepidopterología. 3. e44714–e44714. 11 indexed citations
10.
Morales, Gianmarco De Francisci, Laëtitia Gauvin, Kyriaki Kalimeri, et al.. (2021). Detecting adherence to the recommended childhood vaccination schedule from user-generated content in a US parenting forum. PLoS Computational Biology. 17(4). e1008919–e1008919. 6 indexed citations
11.
Starnini, Michele, Alberto Aleta, Michele Tizzoni, & Yamir Moreno. (2021). Impact of data accuracy on the evaluation of COVID-19 mitigation policies. SHILAP Revista de lepidopterología. 3. 13 indexed citations
12.
Cinelli, Matteo, Gianmarco De Francisci Morales, Alessandro Galeazzi, Walter Quattrociocchi, & Michele Starnini. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences. 118(9). 891 indexed citations breakdown →
13.
Starnini, Michele, et al.. (2021). Modeling partial lockdowns in multiplex networks using partition strategies. QRU Quaderns de Recerca en Urbanisme. 9 indexed citations
14.
Baumann, Fabian, Philipp Lorenz-Spreen, Igor M. Sokolov, & Michele Starnini. (2020). Modeling Echo Chambers and Polarization Dynamics in Social Networks. Physical Review Letters. 124(4). 48301–48301. 229 indexed citations breakdown →
15.
Gozzi, Nicolò, Michele Tizzani, Michele Starnini, et al.. (2020). Collective Response to Media Coverage of the COVID-19 Pandemic on Reddit and Wikipedia: Mixed-Methods Analysis. Journal of Medical Internet Research. 22(10). e21597–e21597. 94 indexed citations
16.
Starnini, Michele, et al.. (2017). Navigability of temporal networks in hyperbolic space. Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona). 15 indexed citations
17.
Starnini, Michele, James P. Gleeson, & Marián Boguñá. (2017). Equivalence between Non-Markovian and Markovian Dynamics in Epidemic Spreading Processes. Physical Review Letters. 118(12). 128301–128301. 42 indexed citations
18.
Starnini, Michele, Mattia Frasca, & Andrea Baronchelli. (2016). Emergence of metapopulations and echo chambers in mobile agents. Scientific Reports. 6(1). 31834–31834. 37 indexed citations
19.
Starnini, Michele, et al.. (2016). Aging and percolation dynamics in a Non-Poissonian temporal network model. Physical review. E. 94(2). 22316–22316. 6 indexed citations
20.
Starnini, Michele & Romualdo Pastor‐Satorras. (2013). Topological properties of a time-integrated activity-driven network. Physical Review E. 87(6). 62807–62807. 48 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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