A magazine where the digital world meets the real world.
On the web
- Home
- Browse by date
- Browse by topic
- Enter the maze
- Follow our blog
- Follow us on Twitter
- Resources for teachers
- Subscribe
In print
What is cs4fn?
- About us
- Contact us
- Partners
- Privacy and cookies
- Copyright and contributions
- Links to other fun sites
- Complete our questionnaire, give us feedback
Search:
News from Twitter
by Paul Curzon, Queen Mary University of London
Having reliable news always matters to us: whether when disasters strike, of knowing for sure what our politicians really said, or just knowing what our favourite celebrity is up to. Nowadays social networks like Twitter are a place to find breaking news, though telling fact from fake-news is getting ever harder, and how do you know where to look?
Sameena Shah leads a research team at news provider Thomson Reuters. They provide trusted information for news organisations worldwide. To help ensure we all have fast, reliable news, Sameena’s team have created a program to automatically discover news from the mass of social networking information that is constantly being generated. It combines programs that process and understand language to work out the meaning of people’s posts - ‘natural language processing’ - with machine learning programs that look for patterns in all the data to work out what is really news. Sameena’s work is helping make sure we all know what’s really happening.