arXiv subjects

Giulio Pecile

Publications and source records attributed to Giulio Pecile.

4 recordsLinked to original sources

arXiv2026

Persistent Structural Inequality of Online Interactions Across Platforms

User interactions on social media platforms are unevenly distributed: a small subset of users consistently captures most of the activity, while the majority remains marginal. Although this pattern is well known and often described by power-law distributions, its consistency across time, platforms, and interaction types has not been systematically assessed. In this study, we analyze user-post bipartite networks from multiple social media platforms. We consider both active contributions (posts) and passive engagement (likes and comments), and quantify distributional properties and inequality using a KL-divergence-based model comparison, an inverse coefficient of variation, and a log-transformed Gini index. Our results show that interaction inequality remains stable over time within each platform. This holds across systems with different sizes, topical focuses, and governance models. These findings indicate that inequality in online engagement is not incidental but reflects structural constraints that shape how visibility and participation are distributed in digital environments.

cs.SI↗

arXiv2025

Patterns, Models, and Challenges in Online Social Media: A Survey

The rise of digital platforms has enabled the large scale observation of individual and collective behavior through high resolution interaction data. This development has opened new analytical pathways for investigating how information circulates, how opinions evolve, and how coordination emerges in online environments. Yet despite a growing body of research, the field remains fragmented and marked by methodological heterogeneity, limited model validation, and weak integration across domains. This survey offers a systematic synthesis of empirical findings and formal models. We examine platform-level regularities, assess the methodological architectures that generate them, and evaluate the extent to which current modeling frameworks account for observed dynamics. The goal is to consolidate a shared empirical baseline and clarify the structural constraints that shape inference in this domain, laying the groundwork for more robust, comparable, and actionable analyses of online social systems.

cs.SI↗

arXiv2024

Decoding Political Polarization in Social Media Interactions

Social media platforms significantly influence ideological divisions by enabling users to select information that aligns with their beliefs and avoid opposing viewpoints. Analyzing approximately 47 million Facebook posts, this study investigates the interactions of around 170 million users with news pages, revealing distinct patterns based on political orientations. While users generally prefer content that reflects their political biases, the extent of engagement varies even among individuals with similar ideological leanings. Specifically, political biases heavily influence commenting behaviors, particularly among users leaning towards the center-left and the right. Conversely, the 'likes' from center-left and centrist users are more indicative of their political affiliations. This research illuminates the complex relationship between social media behavior and political polarization, offering new insights into the manifestation of ideological divisions online.

cs.SI↗

arXiv2024

Mapping the Global Election Landscape on Social Media in 2024

In 2024, half of the global population is expected to participate in elections, offering researchers a unique opportunity to study online information diffusion and user behavior. This study investigates the media landscape on social media by analyzing Facebook posts from national political parties and major news agencies across Europe, Mexico, and India. Our methodology identifies key topics and evaluates public interaction, reflecting broader trends in political engagement. Using Principal Component Analysis, we distil these topics to uncover patterns of correlation and differentiation. This approach reveals dominant themes that engage global audiences, providing critical insights into the interplay between public opinion and digital narratives during a major electoral cycle. Our findings highlight how different topics resonate across political spectrums, shaping political debate and offering a comprehensive view of the interaction between media content, political ideology, and audience engagement.

cs.SI↗