arXiv subjects

Floriana Gargiulo

Publications and source records attributed to Floriana Gargiulo.

At least 19 recordsLinked to original sources

arXiv2026

The geopolitics of knowledge: tipping points, national fingerprints, and the unequal globalization of science

Science is often portrayed as a universal and self-contained system, driven solely by the internal logic of knowledge accumulation and isolated from the turbulences of the socio-political world. In this paper, we challenge this narrative by providing systematic quantitative evidence that the global scientific ecosystem is deeply shaped by geopolitical transformations. Using a large-scale dataset of scientific publications drawn from the OpenAlex database, spanning over five decades and covering virtually all countries and disciplinary areas, we track the evolution of national research profiles and show that geopolitical dynamics shape scientific agendas at multiple scales. At the global level, intrinsic scientific change is slow and cumulative, but exogenous shocks, such as Chernobyl, September 11, and COVID-19, produce rapid disruptions that synchronously reconfigure the priorities of many countries at once. At the country level, we document a broad globalization of knowledge, yet deeply heterogeneous: while Global North countries converge toward a shared international agenda, Global South countries display strong dependence on international resources alongside locally distinctive research interests. Among emerging Southern economies, scientific power is increasingly asserted through specialized and independent agendas. Finally, we observe a reorganization of global scientific influence toward a more polycentric structure, with the emergence of a Southern cluster gravitating around Brazil and Indonesia as new regional hubs.

physics.soc-ph↗

arXiv2025

The Gerontocratization of Science: How hypergrowth reshapes knowledge circulation

Scientific literature has been growing exponentially for decades, with publications from the last twenty years now comprising 60% of all academic output. While the impact of information overload on news and social-media consumption is well-documented, its consequences on scientific progress remain understudied. Here, we investigate how this rapid expansion affects the circulation and exploitation of scientific ideas. Unlike other cultural domains, science is experiencing a decline in the proportion of highly influential papers and a slower turnover in its canons. This results in the disproportionate persistence of established works, a phenomenon we term the ``gerontocratization of science''. To test whether hypergrowth drives this trend, we develop a generative citation model that incorporates random discovery, cumulative advantage, and exponential growth of the scientific literature. Our findings reveal that as scientific output expands exponentially, gerontocratization emerges and intensifies, reducing the influence of new research. Recognizing and understanding this mechanism is crucial for developing targeted strategies to sustain intellectual dynamism and ensure a balanced and healthy renewal of scientific knowledge.

cs.DL↗

arXiv2024

Epistemic integration and social segregation of AI in neuroscience

In recent years, Artificial Intelligence (AI) shows a spectacular ability of insertion inside a variety of disciplines which use it for scientific advancements and which sometimes improve it for their conceptual and methodological needs. According to the transverse science framework originally conceived by Shinn and Joerges, AI can be seen as an instrument which is progressively acquiring a universal character through its diffusion across science. In this paper we address empirically one aspect of this diffusion, namely the penetration of AI into a specific field of research. Taking neuroscience as a case study, we conduct a scientometric analysis of the development of AI in this field. We especially study the temporal egocentric citation network around the articles included in this literature, their represented journals and their authors linked together by a temporal collaboration network. We find that AI is driving the constitution of a particular disciplinary ecosystem in neuroscience which is distinct from other subfields, and which is gathering atypical scientific profiles who are coming from neuroscience or outside it. Moreover we observe that this AI community in neuroscience is socially confined in a specific subspace of the neuroscience collaboration network, which also publishes in a small set of dedicated journals that are mostly active in AI research. According to these results, the diffusion of AI in a discipline such as neuroscience didn't really challenge its disciplinary orientations but rather induced the constitution of a dedicated socio-cognitive environment inside this field.

physics.soc-ph↗

arXiv2023

PubPeer and Self-Correction of Science: Male-Led Publications More Prone to Retraction

This article has a dual objective. Firstly, it aims to investigate whether gender diversity in publications reviewed on Pubpeer has an impact on the (non)retraction of those publications. Secondly, it seeks to analyze the reasons for retractions and examine if there are disparities in retractions based on male-female collaborations. To achieve this, the study utilized a sample of 93,563 publications discussed on Pubpeer spanning the period from 2012 to 2021. The findings reveal that among the reviewed publications, 5% (4,513) were retracted. The concentration index and regression results indicate that publications authored solely by men or led by male authors are 20% to 29% more likely to be retracted compared to those authored solely by women. Regarding the reasons for retractions, the results show that regardless of gender, authors, when working alone, are more prone to engaging in activities such as fake peer review or plagiarism. Women are more concentrated in image manipulation and data errors, while men are more involved in article duplication. Furthermore, the results demonstrate an inverse relationship between the number of authors and retractions, suggesting that a higher number of authors may facilitate better publication control and reduce the temptation for misconduct.

physics.soc-ph↗

arXiv2023

Streetlight Effect in Post-Publication Peer Review: Are Open Access Publications More Scrutinized?

The Streetlight Effect represents an observation bias that occurs when individuals search for something only where it is easiest to look. Despite the significant development of Post-Publication Peer Review (PPPR) in recent years, facilitated in part by platforms such as PubPeer, existing literature has not examined whether PPPR is affected by this type of bias. In other words, if the PPPR mainly concerns publications to which researchers have direct access (eg to analyze image duplications, etc.). In this study, we compare the Open Access (OA) structures of publishers and journals among 51,882 publications commented on PubPeer to those indexed in OpenAlex database (\#156,700,177). Our findings indicate that OA journals are 33% more prevalent in PubPeer than in the global total (52% for the most commented journals). This result can be attributed to disciplinary bias in PubPeer, with overrepresentation of medical and biological research (which exhibits higher levels of openness). However, after normalization, the results reveal that PPPR does not exhibit a Streetlight Effect, as OA publications, within the same discipline, are on average 16% less prevalent in PubPeer than in the global total. These results suggest that the process of scientific self-correction operates independently of publication access status.

cs.DL↗

arXiv2023

Temporal and geographic analysis of the Hydroxychloroquine controversy in the French Twittosphere

At the beginning of the COVID-19 pandemic, the urge to find a cure triggered an international race to repurpose known drugs. Chloroquine, and next Hydroxychloroquine, emerged quickly as a promising treatment. While later clinical studies demonstrated its inefficacy and possible dangerous side effects, the drug caused heated and politicized debates at an international scale, and social media appeared to play a crucial role in those controversies. Nevertheless, the situation was largely different between countries. While some of them rejected quickly this treatment as France, others relied on it for their national policies, as Brazil. There is a need to better understand how such international controversies unfold in different national context. To study the relation between the international controversy and its national dynamics, we analyze those debates on Hydroxychloroquine on the French-speaking part of Twitter, focusing on the relation between francophone European and African countries. The analysis of the geographic dimension of the debate revealed the information flow across countries through Twitter's retweet hypergraph. Tensor decomposition of hashtag use across time points out that debates are linked to the local political choices. We demonstrate that the controversial debates find their center in Europe, in particular in France, while francophone Africa has a lower participation to the debates, following their early adoption of the familiar Hydroxychloroquine and rejection of WHO recommendations.

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arXiv2023

Questioning the impact of AI and interdisciplinarity in science: Lessons from COVID-19

Artificial intelligence (AI) has emerged as one of the most promising technologies to support COVID-19 research, with interdisciplinary collaborations between medical professionals and AI specialists being actively encouraged since the early stages of the pandemic. Yet, our analysis of more than 10,000 papers at the intersection of COVID-19 and AI suggest that these collaborations have largely resulted in science of low visibility and impact. We show that scientific impact was not determined by the overall interdisciplinarity of author teams, but rather by the diversity of knowledge they actually harnessed in their research. Our results provide insights into the ways in which team and knowledge structure may influence the successful integration of new computational technologies in the sciences.

cs.CY↗

arXiv2022

A meso-scale cartography of the AI ecosystem

In recent decades the set of knowledge, tools and practices, collectively referred to as "artificial intelligence" (AI), have become a mainstay of scientific research. Artificial intelligence techniques have not only developed enormously within their native areas of development (computer science, mathematics and statistics) but have also spread fast, in terms of application, to multiple areas of science and technology. In this paper we conduct a large scale analysis of artificial intelligence in science. The first question we address is the composition of what is commonly labeled AI, and how the various elements belonging to this domain are linked together. We reconstruct the internal structure of the AI ecosystem through the co-occurrence network of AI terms in publications' abstracts and title, and we propose to distinguish between 15 different specialities of AI, with different temporal patterns. Further, we investigate the spreading of AI outside its native disciplines. We reconstruct the temporal dynamics of the diffusion of AI production in the whole scientific ecosystem and we describe the disciplinary landscape of AI applications. Finally we take a further step analyzing the role of collaborations for the interdisciplinary spreading of AI techniques. While the study of science frequently emphasizes the openness of scientific communities, we show that there are rarely any collaborations between those scholars who primarily develop AI, and those who apply it. Only a small group of researchers is able to gradually establish a bridge between these communities.

physics.soc-ph↗

arXiv2022

Doing data science with platforms crumbs: an investigation into fakes views on YouTube

This paper contributes to the ongoing discussions on the scholarly access to social media data, discussing a case where this access is barred despite its value for understanding and countering online disinformation and despite the absence of privacy or copyright issues. Our study concerns YouTube's engagement metrics and, more specifically, the way in which the platform removes "fake views" (i.e., views considered as artificial or illegitimate by the platform). Working with one and a half year of data extracted from a thousand French YouTube channels, we show the massive extent of this phenomenon, which concerns the large majority of the channels and more than half the videos in our corpus. Our analysis indicates that most fakes news are corrected relatively late in the life of the videos and that the final view counts of the videos are not independent from the fake views they received. We discuss the potential harm that delays in corrections could produce in content diffusion: by inflating views counts, illegitimate views could make a video appear more popular than it is and unwarrantedly encourage its human and algorithmic recommendation. Unfortunately, we cannot offer a definitive assessment of this phenomenon, because YouTube provides no information on fake views in its API or interface. This paper is, therefore, also a call for greater transparency by YouTube and other online platforms about information that can have crucial implications for the quality of online public debate.

cs.SI↗

arXiv2022

Assessing the influence of French vaccine critics during the two first years of the COVID-19 pandemic

When the threat of COVID-19 became widely acknowledged, many hoped that this epidemic would squash "the anti-vaccine movement". However, when vaccines started arriving in rich countries at the end of 2020, it appeared that vaccine hesitancy might be an issue even in the context of this major epidemic. Does it mean that the mobilization of vaccine-critical activists on social media is one of the main causes of this reticence to vaccinate against COVID-19? In this paper, we wish to contribute to current work on vaccine hesitancy during the COVID-19 epidemic by looking at one of the many mechanisms which can cause reticence towards vaccines: the capacity of vaccine-critical activists to influence a wider public on social media. We analyze the evolution of debates over the COVID-19 vaccine on the French Twittosphere, during two first years of the pandemic, with a particular attention to the spreading capacity of vaccine-critical websites. We address two main questions: 1) Did vaccine-critical contents gain ground during this period? 2) Who were the central actors in the diffusion of these contents? While debates over vaccines experienced a tremendous surge during this period, the share of vaccine-critical contents in these debates remains stable except for a limited number of short periods associated with specific events. Secondly, analyzing the community structure of the re-tweets hyper-graph, we reconstruct the mesoscale structure of the information flows, identifying and characterizing the major communities of users. We analyze their role in the information ecosystem: the largest right-wing community has a typical echo-chamber behavior collecting all the vaccine-critical tweets from outside and recirculating it inside the community. The smaller left-wing community is less permeable to vaccine-critical contents but, has a large capacity to spread it once adopted.

physics.soc-ph↗

arXiv2021

A collaborative path to scientific discovery: Distribution of labor, productivity and innovation in collaborative science

In this work we dig into the process of scientific discovery by looking at a yet unexploited source of information: Polymath projects. Polymath projects are an original attempt to collectively solve mathematical problems in an online collaborative environment. To investigate the Polymath experiment, we analyze all the posts related to the projects that arrived to a peer reviewed publication with a particular attention to the organization of labor and the innovations originating from the author contributions. We observe that a significant presence of sporadic contributor boosts the productivity of the most active users and that productivity, in terms of number of posts, grows super-linearly with the number of contributors. When it comes to innovation in large scale collaborations, there is no exact rule determining, a priori, who the main innovators will be. Sometimes, serendipitous interactions by sporadic contributors can have a large impact on the discovery process and a single post by an occasional participant can steer the work into a new direction.

physics.soc-ph↗

arXiv2020

The Rhythms of the Night: increase in online night activity and emotional resilience during the Spring 2020 Covid-19 lockdown

Context. The lockdown orders established in multiple countries in response to the Covid-19 pandemics are arguably one of the most widespread and deepest shock experienced by societies in recent years. Studying their impact trough the lens of social media offers an unprecedented opportunity to understand the susceptibility and the resilience of human activity patterns to large-scale exogenous shocks. Firstly, we investigate the changes that this upheaval has caused in online activity in terms of time spent online, themes and emotion shared on the platforms, and rhythms of content consumption. Secondly, we examine the resilience of certain platform characteristics, such as the daily rhythms of emotion expression. Data. Two independent datasets about the French cyberspace: a fine-grained temporal record of almost 100 thousand YouTube videos and a collection of 8 million Tweets between February 17 and April 14, 2020. Findings. In both datasets we observe a reshaping of the circadian rhythms with an increase of night activity during the lockdown. The analysis of the videos and tweets published during lockdown shows a general decrease in emotional contents and a shift from themes like work and money to themes like death and safety. However, the daily patterns of emotions remain mostly unchanged, thereby suggesting that emotional cycles are resilient to exogenous shocks.

physics.soc-ph↗

arXiv2020

Junk News Bubbles: Modelling the Rise and Fall of Attention in Online Arenas

In this paper, we present a type of media disorder which we call "`junk news bubbles" and which derives from the effort invested by online platforms and their users to identify and share contents with rising popularity. Such emphasis on trending matters, we claim, can have two detrimental effects on public debates: first, it shortens the amount of time available to discuss each matter; second it increases the ephemeral concentration of media attention. We provide a formal description of the dynamic of junk news bubbles, through a mathematical exploration the famous "public arenas model" developed by Hilgartner and Bosk in 1988. Our objective is to describe the dynamics of the junk news bubbles as precisely as possible to facilitate its further investigation with empirical data.

cs.SI↗

arXiv2020

Can gender inequality be created without inter-group discrimination?

Understanding human societies requires knowing how they develop gender hierarchies which are ubiquitous. We test whether a simple agent-based dynamic process could create gender inequality. Relying on evidence of gendered status concerns, self-construals, and cognitive habits, our model included a gender difference in how responsive male-like and female-like agents are to others' opinions about the level of esteem for someone. We simulate a population who interact in pairs of randomly selected agents to influence each other about their esteem judgments of self and others. Half the agents are more influenced by their relative status rank during the interaction than the others. Without prejudice, stereotypes, segregation, or categorization, our model produces inter-group inequality of self-esteem and status that is stable, consensual, and exhibits characteristics of glass ceiling effects. Outcomes are not affected by relative group size. We discuss implications for group orientation to dominance and individuals' motivations to exchange.

physics.soc-ph↗

arXiv2020

Asymmetric participation of defenders and critics of vaccines to debates on French-speaking Twitter

For more than a decade, doubt about vaccines has become an increasingly important global issue. Polarization of opinions on this matter, especially through social media, has been repeatedly observed, but details about the balance of forces are left unclear. In this paper, we analyse the flow of information on vaccines on the French-speaking realm of Twitter between 2016 and 2017. Two major asymmetries appear. Rather than opposing themselves on each vaccine-related controversy, pro and anti-vaccine accounts focus on different vaccines and vaccine-related topics. Pro-vaccine accounts focus on hopes for new groundbreaking vaccines and on ongoing outbreaks of vaccine-preventable illnesses. Vaccine critics concentrate their posts on a limited number of controversial vaccines and adjuvants. Furthermore, vaccine-critical accounts display greater craft and energy, using a wider variety of sources, and a more coordinated set of hashtags. This double asymmetry can have serious consequences. Despite the presence of a large number of pro-vaccine accounts, some arguments raised by efficiently organized and very active vaccine-critical activists are left unanswered.

physics.soc-ph↗

arXiv2018

The anatomy of a Web of Trust: the Bitcoin-OTC market

Bitcoin-otc is a peer to peer (over-the-counter) marketplace for trading with bit- coin crypto-currency. To mitigate the risks of the p2p unsupervised exchanges, the establishment of a reliable reputation systems is needed: for this reason, a web of trust is implemented on the website. The availability of all the historic of the users interaction data makes this dataset a unique playground for studying reputation dynamics through others evaluations. We analyze the structure and the dynamics of this web of trust with a multilayer network approach distin- guishing the rewarding and the punitive behaviors. We show that the rewarding and the punitive behavior have similar emergent topological properties (apart from the clustering coefficient being higher for the rewarding layer) and that the resultant reputation originates from the complex interaction of the more regular behaviors on the layers. We show which are the behaviors that correlate (i.e. the rewarding activity) or not (i.e. the punitive activity) with reputation. We show that the network activity presents bursty behaviors on both the layers and that the inequality reaches a steady value (higher for the rewarding layer) with the network evolution. Finally, we characterize the reputation trajectories and we identify prototypical behaviors associated to three classes of users: trustworthy, untrusted and controversial.

cs.CY↗

arXiv2016

The classical origin of modern mathematics

The aim of this paper is to study the historical evolution of mathematical thinking and its spatial spreading. To do so, we have collected and integrated data from different online academic datasets. In its final stage, the database includes a large number (N~200K) of advisor-student relationships, with affiliations and keywords on their research topic, over several centuries, from the 14th century until today. We focus on two different topics, the evolving importance of countries and of the research disciplines over time. Moreover we study the database at three levels, its global statistics, the mesoscale networks connecting countries and disciplines, and the genealogical level.

math.HO↗

arXiv2015

Can topology reshape segregation patterns?

We consider a metapopulation version of the Schelling model of segregation over several complex networks and lattice. We show that the segregation process is topology independent and hence it is intrinsic to the individual tolerance. The role of the topology is to fix the places where the segregation patterns emerge. In addition we address the question of the time evolution of the segregation clusters, resulting from different dynamical regimes of a coarsening process, as a function of the tolerance parameter. We show that the underlying topology may alter the early stage of the coarsening process, once large values of the tolerance are used, while for lower ones a different mechanism is at work and it results to be topology independent.

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