This paper presents a dual analysis of critical information flows on peer-to-peer (P2P) networks, focusing on two distinct datasets: cyberwar-related leaks from the Russo-Ukrainian conflict and unregulated firearm blueprints, commonly known as "ghost guns." Through a longitudinal study spanning 2018-2024, we examine the geographic distribution, temporal persistence, and network dynamics of these data flows, investigating how historical events shape their dissemination. Using alpha60, a custom P2P tracking system, we oversampled swarms at four-minute intervals, aggregating unique peer and seed data into hourly and weekly time-series units. Our analysis reveals significant year-over-year increases in both datasets, with cyberwar leaks peaking at 20.7M unique downloads in 2024 and ghost gun files at 9.9M unique downloads the same year.

Geopolitical disruptions, including the death of Alexei Navalny (2024) and the Kremlin’s information warfare tactics, correlate with spikes in cyberwar leaks. Similarly, domestic unrest and regulatory shifts impact ghost gun circulation patterns. Comparing these distributions to media consumption trends, we highlight key differences in P2P engagement with politically and legally sensitive content. Our findings contribute to broader discussions on information warfare, digital sovereignty, and the ethics of decentralized data flows. This research advances methodologies for analyzing P2P network behavior and underscores the geopolitical and security implications of unregulated information dissemination in digital ecosystems.

The Fediverse, a decentralized network of social platforms interconnected via protocols like ActivityPub, has gained traction amid crises in centralized platforms, such as Elon Musk’s acquisition of Twitter/X in 2023 and Meta’s 2025 changes in content moderation". This migration, termed “decentralized replatforming,” represents a horizontal shift where users voluntarily leave toxic spaces for federated networks like Mastodon and Pixelfed. While decentralization allows customizable moderation rules, it also creates challenges in scalability, resource allocation, and combating disinformation. This study investigates these tensions through semi-structured interviews with maintainers of Fediverse instances (Hubzilla.com.br, Bolha, Milpa), focusing on governance, costs, and ethical dilemmas. Preliminary findings reveal a heterogeneous migration: Bolha attracts progressive users fleeing hate speech, while Hubzilla serves as a technical refuge. The research proposes “decentralized replatforming” as a concept capturing both escape from corporate platforms and experimentation with alternative models. Key challenges include balancing autonomy with collective responsibility and ensuring sustainability without replicating Big Tech’s centralization. The study highlights the Fediverse as a contested space for ethical and technical innovation in digital communication.

As much as the debate around contemporary information flows and its associated risks has advanced in the last years—specially through the consolidation of an “information integrity” agenda—there are still significative gaps in literature concerning how digital platform usage affects the access to reliable, diverse and evidence-based information. Building on this, the present article aims to contribute to the discussion on how digital platforms’ big data algorithmic infrastructures relate to the promotion of healthy and diverse informational ecosystems. It draws upon existing sociological literature about algorithmic systems and on accumulated knowledge from international discussions (regarding the elaboration of an information integrity-oriented survey) to build an “investigation matrix”, proposing pathways for future practical quantitative and qualitative research in the field. Among its many conclusions, the matrix reinforces the need for a more holistic articulation of efforts on the theme, as well as the importance of multidisciplinary research that encompasses both the technical and social aspects of the phenomena. The article also discusses the importance of digital platforms in aiding researchers and policymakers with access to data, enabling impactful research efforts in the field.

This study introduces a framework to identify opinion leaders on Telegram, adapting a methodology developed for Twitter. The work is motivated by the need to examine influence dynamics on hybrid platforms like Telegram, where platform affordances can potentially facilitate the spread of disinformation and polarizing discourse. Specifically, the traceability of forwarded messages provides analytical possibilities for understanding these complex communication networks. The analysis involves a case study conducted with data extracted from public groups supporting Jair Bolsonaro's presidential re-election campaign. Using network analysis techniques, the method maps key roles including influencers, conversation starters, active engagers, and network creators. Results highlight these actors' roles in shaping information circulation within Telegram's public groups and channels. The discussion emphasizes the framework's systematic approach to analyzing opinion leadership. This research contributes to understanding how hybrid social platforms facilitate influence and information dissemination, offering practical tools for researchers studying emerging social media ecosystems.