arXiv subjects

Maddalena Torricelli

Publications and source records attributed to Maddalena Torricelli.

7 recordsLinked to original sources

arXiv2026

Harder, shorter, sharper, forward: A comparison of women's and men's elite football gameplay (2020-2025)

Elite football is believed to have evolved in recent years, yet systematic evidence for the pace and form of that change remains sparse. Drawing on event-level records for 13,018 matches across ten top-tier men's and women's leagues in England, Spain, Germany, Italy, and the United States (2020-2025), we quantify match dynamics through two complementary lenses: conventional performance statistics and pitch-passing networks that track ball movement across spatial regions of the field. Between 2020 and 2025, average passing volume, pass accuracy, and the proportion of passes made under pressure all increased, with the largest year-on-year changes occurring in women's competitions. Network measures reveal that normalized outreach decreased, indicating teams increasingly concentrate ball circulation into shorter-range passing connections rather than wide spatial distribution. These trends are consistent across countries and tiers, yet persistent national differences indicate that stylistic diversity remains. Notably, women's competitions exhibit stronger rates of change across most metrics, consistent with an accelerating professionalization, while the systematic decline in network outreach across all competitions points to a sport-wide tactical convergence toward shorter, more concentrated passing structures.

physics.soc-ph↗

arXiv2025

Temporal dynamics of goal scoring in soccer

We investigated the temporal distribution of goals in soccer using event-level data from 3,433 matches across 21 leagues and competitions. Contrary to the prevailing notion of randomness, we found that the probability of a goal being scored is higher as matches progress, and we observed fewer-than-expected goals in the early minutes of each half. Further analysis of the time between subsequent goals shows an exponential decay, indicating that most goals naturally cluster closer together in time. By splitting this distribution by the team that scores the next goal, we observe bursty goal-scoring dynamics, wherein the same team is more likely to score again shortly after its previous goal. These findings highlight the importance of match context (whether driven by fatigue, tactical adaptations, or psychological momentum) in shaping when teams are able to score. Moreover, the results open avenues for extending data-driven methods for identifying high-impact moments in a match and refining strategic decision-making in soccer's evolving analytical landscape.

physics.soc-ph↗

arXiv2024

The role of interface design on prompt-mediated creativity in Generative AI

Generative AI for the creation of images is becoming a staple in the toolkit of digital artists and visual designers. The interaction with these systems is mediated by \emph{prompting}, a process in which users write a short text to describe the desired image's content and style. The study of prompts offers an unprecedented opportunity to gain insight into the process of human creativity. Yet, our understanding of how people use them remains limited. We analyze more than 145,000 prompts from the logs of two Generative AI platforms (Stable Diffusion and Pick-a-Pic) to shed light on how people \emph{explore} new concepts over time, and how their exploration might be influenced by different design choices in human-computer interfaces to Generative AI. We find that users exhibit a tendency towards exploration of new topics over exploitation of concepts visited previously. However, a comparative analysis of the two platforms, which differ both in scope and functionalities, reveals some stark differences. Features diverting user focus from prompting and providing instead shortcuts for quickly generating image variants are associated with a considerable reduction in both exploration of novel concepts and detail in the submitted prompts. These results carry direct implications for the design of human interfaces to Generative AI and raise new questions regarding how the process of prompting should be aided in ways that best support creativity.

cs.CY↗

arXiv2023

Beyond Active Engagement: The Significance of Lurkers in a Polarized Twitter Debate

The emergence of new public forums in the shape of online social media has introduced unprecedented challenges to public discourse, including polarization, misinformation, and the emergence of echo chambers. While existing research has extensively studied the behavior of active users within echo chambers, little attention has been given to the hidden audience, also known as lurkers, who passively consume content without actively engaging. This study aims to estimate the share of the hidden audience and investigate their interplay with the echo chamber effect. Using Twitter as a case study, we analyze a polarized political debate to understand the engagement patterns and factors influencing the hidden audience's presence. Our findings reveal a relevant fraction of users that consume content without active interaction, which underscores the importance of considering their presence in online debates. Notably, our results indicate that the engagement of the hidden audience is primarily influenced by factors such as the reliability of media sources mentioned in tweets rather than the ideological stance of the user that produced the content. These findings highlight the need for a comprehensive understanding of the hidden audience's role in online debates and how they may influence public opinion.

cs.SI↗

arXiv2023

Hurricanes Increase Climate Change Conversations on Twitter

The public understanding of climate change plays a critical role in translating climate science into climate action. In the public discourse, climate impacts are often discussed in the context of extreme weather events. Here, we analyse 65 million Twitter posts and 240 thousand news media articles related to 18 major hurricanes from 2010 to 2022 to clarify how hurricanes impact the public discussion around climate change. First, we analyse news content and show that climate change is the most prominent non-hurricane specific topic discussed by the news media in relation to hurricanes. Second, we perform a comparative analysis between reliable and questionable news media outlets, finding that the language around climate change varies between news media providers. Finally, using geolocated data, we show that accounts in regions affected by hurricanes discuss climate change at a significantly higher rate than accounts in unaffected areas, with references to climate change increasing by, on average, 80% after impact, and up to 200% for the largest hurricanes. Our findings demonstrate how hurricanes have a key impact on the public awareness of climate change.

physics.soc-ph↗

arXiv2022

Growing polarisation around climate change on social media

Climate change and political polarisation are two of the 21st century's critical socio-political issues. Here, we investigate their intersection by studying the discussion around the UN Conference of The Parties on Climate Change (COP) using Twitter data from 2014 to 2021. First, we reveal a large increase in ideological polarisation during COP26, following low polarisation between COP20 and COP25. Second, we show that this increase is driven by growing right-wing activity, a 4-fold increase since COP21 relative to pro-climate groups. Finally, we identify a broad range of ''climate contrarian'' views during COP26, emphasising the theme of ''political hypocrisy'' as a topic of cross-ideological appeal; contrarian views and accusations of hypocrisy have become key themes in the Twitter climate discussion since 2019. With future climate action reliant on negotiations at COP27 and beyond, our results highlight the importance of monitoring polarisation, and its impacts, in the public climate discourse.

physics.soc-ph↗

arXiv2019

weg2vec: Event embedding for temporal networks

Network embedding techniques are powerful to capture structural regularities in networks and to identify similarities between their local fabrics. However, conventional network embedding models are developed for static structures, commonly consider nodes only and they are seriously challenged when the network is varying in time. Temporal networks may provide an advantage in the description of real systems, but they code more complex information, which could be effectively represented only by a handful of methods so far. Here, we propose a new method of event embedding of temporal networks, called weg2vec, which builds on temporal and structural similarities of events to learn a low dimensional representation of a temporal network. This projection successfully captures latent structures and similarities between events involving different nodes at different times and provides ways to predict the final outcome of spreading processes unfolding on the temporal structure.

physics.soc-ph↗