NewsQ design thinking activities are focused on three main outcomes: (1) technical definitions, (2)“ideation” through data, and (3) creative prototypes.
In our mission to improve news ranking and recommendation systems, NewsQ asks journalists, researchers and technologists to use journalistic standards and civic frameworks to clarify how news should be defined and framed for online realms.
Since algorithms operate according to defined rules, NewsQ has documented technical definitions around the principles and metrics of online news quality that can be more readily incorporated into algorithmic processing.
➔ Methodological definitions and metrics
Methodological definitions and metrics are proposed in essays and papers, ranging from short, reflective blog pieces that clarify the inquiry around news quality for machine purposes to structured research designs about metrics that can help determine how to assess the state of online news.
• Social Science Research Council NewsQ Call for Papers in 2020 – News Quality in the Platform Era.
➔ Questionnaire related to Vaccine News Quality
As part of the ARTT project, we built a questionnaire that attempts to establish when articles are of greater or lesser quality according to both journalistic and vaccine safety (pharmacovigilance) standards.
➔ Potential news quality “signal” or indicator data definitions
Signals, or potential indicators of information quality or credibility, can include a number of content- and context-related information, such as the emotional valence of content, or the author of an article. When taken in context in combination with other signals or information, these indicators may help point algorithms to higher quality journalism.
• The NewsQ Database contained in 2020 over 100 units of information on over 12,000 news and information sites. Some of these units of information may be potential “signals” of quality journalism. This work has transitioned over to our friends at the Knowledge Futures Group. You can still find past definitions of signal categories, classes, and signals themselves available in our Resources.
Ideations through Data
NewsQ supports the use of data collections to “ideate” or foster new ideas that help clarify what constitutes – and how to define – quality in news ranking and recommendation.
➔Panel Discussions among Journalists In addition to the data mentioned above, we also have created archived screen captures of news ranking and recommendations from various platforms and applications to foster insight. This data is now hosted by our collaboration partner Knowledge Futures Group.
• News Ranking Review Panels. This series of activities brought together journalists to review the archived captures in order to develop practical guidelines for implementing quality news online in platform news products. More about 2020 and 2021 panels is located on this page.
• Methodological Paper defining the News Panel Process. A paper explaining the methodological process of panel formation and results in 2020 was published in Journalism Studies in June 2022. (Published version, accepted version).
➔Seed Grants for Data Projects
In the past, NewsQ offered grants for data projects that may surface journalistic standards for news ranking and recommendation systems. One example recipient is the Markkula Center for Applied Ethics, and their project on journalistic ethics and behavior: How Might We Detect Who Is and Who Is Not Doing Journalism Online?
• Check out the progress of this project in 2022, Journalism Source Diversity Dashboard and Monitor
NewsQ also facilitates solution prototypes to the news ranking and recommendation challenge among people with different interests and backgrounds.
➔Wikipedia Edit-a-thons from the KNoW Science Collaboration
News is an important part of the record for references and histories. NewsQ Knowledge Networks on the Web (KNoW) Science activities are collaborations to understand the interaction between news and reliable science/health information, and to strengthen the profile of this information within online networks of knowledge worldwide.
In partnership with the Vaccine Safety Net, an initiative of the World Health Organization, Wikimedia DC, MuckRock Foundation, the Stanford History Education Group, and others, KNoW Science activities focused on the issue of vaccine safety. Our initial efforts supported the availability of reliable, understandable, evidence-based vaccine safety information on Wikipedia, as well as through news and media literacy efforts.
• See the schedule of past KNoW Science Vaccine Safety trainings and edit-a-thons.
➔Analysis and Response Toolkit for Trust (ARTT)
Out of the KNoW Science collaboration, we worked together with others in 2021-22 on a tool prototype called ARTT (“Analysis and Response for Trust Tool”), to aid community exchanges regarding vaccine efficacy. (ARTT is a separate project that can be found here.)