Getting closer to Data Science — Media Journalism

As the volume of information increases, traditional methodologies and processes of accessing and verifying information are evolving.

At the 2015 General Election, flaws in research methods became apparent after 91 Great Britain wide voting intention polls never predicted the outcome of the Election. This has since created greater scrutiny on the methods of gathering information from data sources.

A Post-Election comment from You Gov went on to say “The difference between the polls and the result was not random sample error — it looks as if there was some deeper methodological failing”

At the recent Data Science for the Media Summit organised by the University of Edinburgh, delegates discussed the use of Data Science as a key digital skill for Media Journalism.

With professionals from BBC, Bloomberg, The Economist, Channel 4 and The New York Times speaking at the Summit, the debate amplified the knowledge gap in data science amongst media professionals.

Jacqui Maher, Interactive Journalist from the BBC News Labs commented, “So we are looking at how we might retain the structure that is in a journalist’s head, as they are writing the story. So digital tools will help journalists during the investigative process”

The discussion across the Summit outlined the need for technologists to develop new methodologies to gather data as well create digital tools and platforms to help Journalists qualify sources of data.

With the creation of The Alan Turing Institute and The Data Lab at the University of Edinburgh, Digital Media SME’s looking to access expertise in Data Science are now encouraged to access the expert support available from both organisations and develop new platforms.

Further Reading from the Data Science for the Media Summit can be found at this link : Nicola Osborne, Jisc MediaHub Service Manager — Edina Blog:

Footnote: This article has been compiled using market insight from PA Consulting Group

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