Data and algorithmic journalism

A few weeks ago I had the opportunity to attend the Data Power conference. The conference focus on the current shift towards modelling social process based on data-driven decisions, and how the era of big data is rapidly shaping the world.

With a great line of keynote speakers (Mark Andrejevic, José van Dijck, Joseph Turow, Evelyn Ruppert, Rob Kitchin), Data Power gathered a great number of researchers and scholars from various fields and disciplines.
Some of the most celebrated topics revolved around surveillance, governance, data labor, and of course, journalism. The current escalation of data use within journalism is reshaping journalistic practice became the center of the discussion. Two main practices seemed to share the spotlight. First Data Journalism, in which data itself is the content. New narrative structures built upon data visualization have started to dominate digital news websites, which changes the way we understand and consume news. Second, algorithmic journalism (also known as robot journalism) focuses on how software is being used in order to generate journalistic content, partly automating the role of the journalist. Of course, robot journalism is still in its infancy, but the advances in language software innovation points to a surge of algorithmic journalism in the near future. This, of course, will have a huge impact on the way news is produced.
Personally, I presented on how journalism has increasingly been quantified both in the way it is been delivered to the public in terms of metrics of consumption, but also in the way those metrics shape how journalists create content. I used the case study of the Bleacher Report, an organization that has gamified the production structure and that measures performance according to different metrics, from number of reads, to number of followers.
It was clear that the trend of algorithmic and data journalism is escalate in the near future. Something we will have to keep an eye on.

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