Authors: Paul Rissen, Lewis Westbury

Tiny problem statement

Some news sources are perceived to be more harmful than others. How do we know whether the content that is created does more good than harm? One way to measure this might be to look at the user needs that articles address.

This is a small hack that you could iterate on...

Tiny exploration of the problem

The smartco user needs model describes a range of user needs for journalism.

What if you tagged and categorised e.g. a teen magazine - which needs are they addressing? Where are the gaps?

For digital news sources, what could you learn from the share rates of articles addressing different needs? Which are the anomalies? Can you use this sort of data to reason about news avoidance?

Tiny suggestion

Build a categoriser for news article needs. This may require you to develop some rules that generative AI can use to determine which needs an article is attempting to meet.

The internet archive has a newspaper category, from which you can download sources

British Library newspaper archive is free to search, contains many types of news

• Obituaries
• Wedding notices
• Letters to the editor
• etc.

You could use the above sources as training data.