BBC News Labs: In-Article Chatbots – Info Gadgets

How can we help less engaged audiences understand big news stories?

The bigger a news story, the harder it gets for the casual reader to understand recent developments.

This is particularly a problem for readers that tend to be less engaged with the news. For example, our research shows younger readers may know that a story is important, but often don’t know where to look for background information. This can make them feel nervous and anxious when they try to engage with current events.

We thought: wouldn’t it be better if readers could simply ask for explanations on the elements of the story that they don’t understand?

Our in-article bots are designed to feel like a conversation with a BBC expert. Users can choose from a list of questions to explore different elements of a story in more depth, based on their interests and current level of understanding of a topic. This prevents readers from feeling overwhelmed by large amounts of text — only some of which may be relevant to their interests.

The bots are embedded within BBC News stories, meaning that readers can find the information they need to understand the latest reporting directly on the article pages themselves.

Our in-article bots have answered readers’ questions on voter registration leading up to the UK general election.

We’ve used them to explain how Open Banking could affect individuals in 2018.

They provide information on the current flu outbreak in the UK.

Credit for our in-article bots goes to: Grant Heinrich, Tom Maslen, Alvin Ourrad, Kevin Peachey, Joy Roxas, Paul Sargeant and Bella Hurrell.