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This article explores the interactions between journalistic actors and emerging open-source intelligence and investigation (OSINT) communities. It employs qualitative content analysis of discourse from two OSINT communities surrounding three events following the Russian invasion of Ukraine in 2022, which received substantial coverage in news media. OSINT practices are rapidly becoming a mainstay of the contemporary political process by allowing ordinary citizens to verify information shared through digital platforms, which is traditionally the societal task assigned to journalism. In doing so, they provide a timely factual baseline for opinion formation and political decision-making. This research explores the role constellations resulting from this shift in verification duties from journalistic actors to amateur online communities on digital platforms and maps the fundamental dynamics involved in OSINT. We analyze how information is received and processed in OSINT communities, how digital platforms facilitate the fact-checking process, and how journalism and OSINT interact. Based on our findings, we develop a theoretical framework that distinguishes between the input, throughput, and output phases of OSINT. Our model contributes to a baseline understanding of the crucial and novel partnership between citizens and journalists on digital platforms.

Scrolling through a social media newsfeed has become almost ubiquitous. Yet, it remains unknown what specific post elements people pay attention to and whether this varies depending on how they access social media newsfeeds. In an eye-tracking experiment among university students ( N = 201), we compare user attention to specific post elements like source, title, or picture, in a dynamic Facebook newsfeed by device (desktop vs. mobile) and smartphone usage environment (private vs. public). Significant attentional differences occur at the level of the newsfeed post elements. Users pay less attention to visual information on the mobile newsfeed and more attention to textual post elements in a public setting.

TikTok is developing into a key platform for news, advertising, politics, online shopping, and entertainment in Germany, with over 20 million monthly users. Especially among young people, TikTok plays an increasing role in their information environment. We provide a human-coded dataset of over 4,000 TikTok videos from German-speaking news outlets from 2023. The coding includes descriptive variables of the videos (e.g., visual style, text overlays, and audio presence) and theory-derived concepts from the journalism sciences (e.g., news values).

This dataset consists of every second video published in 2023 by major news outlets active on TikTok from Germany, Austria, and Switzerland. The data collection was facilitated with the official TikTok API in January 2024. The manual coding took place between September 2024 and December 2024. For a detailed description of the data collection, validation, annotation and descriptive analysis, please refer to [Forthcoming dataset paper publication].