The internet, and social media in particular, has had implications on the way that people consume news. Social media has allowed the rapid spread of fake news, and the formation of ‘echo chambers’, where people only see certain kinds of news. The news that people see on social media, and that people see when they browse news sources themselves, often reaffirms their own opinions.

We aimed to build a tool that addresses this problem.

What it does

Our tool uses machine learning to analyse news articles extracted using Articles are provided tags. If a lot of articles have the same ‘tag’, that tag becomes a ‘trend’ - an important news item, with a lot of sources reporting on it.

We aimed to build a tool that collates news from a lot of sources, extracts important news trends and topics, and shows articles from a range of sources.

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for Orca news


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