An interactive discussion about the characteristics of quality news and how to use these to elevate quality in news recommendations and ranking systems.
What news articles should rise to the top of the feeds that algorithmically distribute journalism to much of the public? The NewsQ initiative has explored the meaning of news quality in news algorithms, with the hypothesis that surfacing quality journalism will also make it more economically viable.
Yet, news quality is a complicated, and not clearly understood concept. There are aspects around which experienced journalists are likely to disagree, depending on the context in question. At the same time, news ranking and recommendation systems are built around specific processes and clear rules that require specificity. For example, if local news or original reporting are important to consider, how might their importance vary according to science news versus a critical disaster?
The question of how we want algorithms to work needs to be grounded in the observations we can make now.
If the journalism community were able to influence the decision making process of news algorithms, how would that work and what would it look like?
Join NewsQ’s team for an interactive discussion focused on news quality in ranking and recommendation systems. Participants will also learn about NewsQ’s Review Panels, which are researching specific cases of news ranking and recommendation to understand whether guidance regarding quality journalism—interpretable by and helpful to both machines and journalists—might emerge.
- Connie Moon Sehat
NewsQ Director, NewsQ - Hacks/Hackers
- Jeff Jarvis
Director of the Tow-Knight Center for Entrepreneurial Journalism, Craig Newmark Graduate School of Journalism (CUNY)