One year on the PLOS ONE Editorial Board: Pierluigi Vellucci

In this interview, we check in with Pierluigi Vellucci, who joined the PLOS ONE Editorial Board a year ago this week. Dr Vellucci discusses his motivations for becoming involved with PLOS ONE, the transformative agreements leading to greater adoption of Open Access publishing, and the versatility of agent-based modeling.

Pierluigi Vellucci is a researcher in Mathematical Methods of Economics, Finance and Actuarial Sciences at the Department of Economics of Roma Tre University. He obtained his Ph.D. in Mathematical Models for Engineering, Electromagnetism, and Nanoscience in 2017 at La Sapienza University of Rome. His most recent research interests include multi-agent systems for the study of public opinion formation and methods of representation theory (frames, Gabor systems, and wavelets) for the analysis of financial series. He has been a visiting professor at the Department of Mathematics and Statistics, Florida International University (Miami), and has authored over 40 scientific publications.

My website: https://pierluigivellucci.com/

My Twitter account: https://twitter.com/PierluigiVellu1

My LinkedIn account: https://www.linkedin.com/in/pierluigi-vellucci-ba9100a0/

My Facebook account: https://www.facebook.com/PierluigiVellucci/

PLOS: Congratulations to one year on the PLOS ONE Editorial Board. What have you learned in the past year about ensuring a fair and thorough review process?

PV: Thank you for the opportunity to reflect on my experience as a member of the PLOS ONE Editorial Board over the past year. Joining the board was a decision I made after carefully reviewing several articles as a peer reviewer. I am a strong advocate for open access and I believe that PLOS ONE is one of the pioneers of open science. So, why not join PLOS ONE and contribute to improving open-access science?

I have been amazed by the central role that peer review plays in the advancement of science. Editors and reviewers act as guardians of science. Being involved in the work of the Editorial Board is a way to be part of this process, and both an honour and a responsibility. Furthermore, from my point of view, it is an opportunity to promote the use of mathematical formalism where possible to analyse and solve complex problems arising from the social sciences.

I have been delighted to be part of the PLOS ONE Editorial Board due to the journal’s emphasis on the technical quality of scientific articles rather than their perceived ‘impact.’ I believe that a reputable open access scientific journal will help people gain a better understanding of the social problems I am addressing through mathematical modeling.

PLOS: You have published a lot of your research on preprints and/or Open Access? What first motivated you to do this? What continues to motivate you to do so?

PV: Thank you for the opportunity to discuss my experience with publishing research on preprints and/or open-access platforms. I have indeed published a significant portion of my research on these platforms, not only journals that are entirely open access but also those that are not but which offer this possibility after acceptance of the paper, thanks in part to transformative agreements signed by the university I am affiliated with (Roma Tre University), in which the costs covered by the institutions not only ensure read access to scientific journals but also include those for open access publication (article processing charges) by affiliated authors.

High impact, equitable access, and rapid turnaround – are the driving factors for me.

Open access is crucial for providing equitable and unrestricted access to high-quality scientific knowledge. PLOS ONE has been at the forefront of the open science movement, enabling free and fair access to cutting-edge research. However, it is essential to maintain high standards, as some open-access journals continue to publish manuscripts of questionable value.

I view Open Access options as an important part of the future of scholarly publishing. It ensures access to information for students and researchers who might not otherwise have the means to obtain it. From this point of view, I think that to reduce inequalities, we must encourage open access.

PLOS: Your research touches upon many different applications, from decision-making to prices of oil and metals. What is it about Agent-Based Models that allow us to model so many different phenomena?

PV: Agent-based modeling is a simulation approach that focuses on the behavior and interactions of individual entities, called agents, within a larger system. Agents can be individuals, organizations, or even abstract entities. The behavior and decision-making processes of agents are typically modeled based on simple rules and heuristics, allowing for the emergence of system-level behaviors. Agent-based models simulate the interactions and dynamics among agents over time in order to understand the patterns and outcomes that emerge from their collective behavior.

Agent-based models often do not assume perfect rationality or complete knowledge on the part of the agents and can capture a wide range of behaviors and interactions.

For example, I can think of a recent published work with my friend and colleague Elisa Iacomini (a researcher at the Department of Mathematics and Computer Science, University of Ferrara), where we hypothesized that a certain type of agent acts contrary (regardless) to the strategy followed by a certain social group, a subgroup of the whole society. Our article represents a virtual experiment, as we defined mathematical laws that agents must follow and conducted numerical simulations. We then compared the simulation results with numerical evidence from real data (specifically, Twitter data in our case). Our work is empirical and preliminary in nature, aimed at understanding which direction to take for future research. There are examples where the predictive value of these models has shown its effectiveness. I would like to mention the models introduced by physicist Serge Galam, widely recognized as a pioneer in the field of sociophysics. His predictions regarding the outcomes of various political elections, such as Trump’s victory in the 2016 presidential election, have made him an internationally renowned figure. However, that is not the central point. In my opinion, agent-based models should not compete with other models, such as machine learning, in an attempt to determine who is better at predicting the future. The power of agent-based models lies in their ability to explain the emergence of social phenomena through the use of simple assumptions about society. In a way, similar to the approach of physicists creating theories to explain the workings of the universe, agent-based models allow for the creation of a theory to understand the functioning of society.

Stay tuned for more content within computer science, mathematics and complex systems at EveryONE over the next few weeks. If you are at the NetSci2023 conference this week, don’t forget to check in with our Senior Editor Hugh Cowley, or to catch talks by many of our Editorial Board members and Guest Editors, including Renaud Lambiotte, Mirta Galesic, Marta Sales-Pardo, Hocine Cherifi, Alberto Aleta, Ceyhun Eksin, Dion O’Neale, Luis M. Rocha, Fabio Saracco, Petter Holme, Fragkiskos Papadopoulos and Tiago Peixoto.

Disclaimer: Views expressed by contributors are solely those of individual contributors, and not necessarily those of PLOS.