COMPUTATIONAL JOURNALISM: Data Driven News Generation and Reporting

Two recent events have motivated the articulation of this article. First is the recent spat of concern over growing fake news and second the controversy that surrounded the differing reports of the attendance of the Trump inauguration. How then can newsrooms address such controversies? The need for news verification is often more pronounced in seasons such as the one where we are entering in of electioneering. Not to mention Opinion polls that form a sizeable chunk of news content leading to election.

One such growing intervention is Computational Journalism. The Computational Journalism a new way to find and tell news stories with, by and about data and algorithms. Journalists working today routinely encounter social and political systems that are driven by new technologies. To critique their operation, a journalist needs an understanding of computation — of the consequences of classification and counting, of the collection and analysis of data, and of the accountability of algorithms. Far from virtual, inert quantities, data and computation exert real forces in the physical world, shaping and defining systems of power that will play larger and larger roles in people's lives.

Journalists, as the explainers of last resort, need to adapt responsibly — finding and creating new kinds of "stories" that respond directly to new technologies, whether that “story” be a piece written in English or in Python, a data visualization, an API or database, an immersive virtual experience, or a sensor drone deployment.

Through adoption of such approaches, journalism is and should be adapting in the face of new technologies. It is a hybridization of journalism and the computing and data sciences.

The electioneering period provides strong use case on how computational journalism can be used to enrich and authentic the quality of news that media houses churn on a daily basis. From opinion polls to understanding the outcome of the election—and how political communication might work in the present and future—we need to begin deploying computational journalism.

In November 2015, the more radical of the two Brexit campaigns, "Leave.EU," supported by Nigel Farage, announced that it had commissioned a Big Data company to support its online campaign. The company's core strength: innovative political marketing—micro targeting—by measuring people's personality from their digital footprints, psychographic modeling. The Trump team commissioned the same company weeks to the USA election and it took credit for turning the odds by nuancing communication to the different profile of voters propelling Trumps to victory. 

Hence, it is unlikely that political polls will disappear from the headlines of political reporting. Instead of simply warning against the dangers of polls or urging journalists to change their model of political reporting, there is need to appreciate the reason behind the crisis of political polls. For instance a proposed remedy might be non-probability polling, in combination with algorithms and Big Data approach, which does have advantages when it comes to a) cost, b) time and c) fine-grained estimates of public opinion.

On the controversy surrounding the Trump inauguration, where there were varied accounts of how many people attended the event, newsrooms could use analysis of photographs and video footage to give a more precise perspective of the situation. With upgrades in technology to turn documents into data that can be readily searched, investigative reporting will be able to take another step forward.

Retrospectively, Computational journalism lowers story discovery and production costs, and makes news sources more efficient in their content creation. Data is not only a source for new stories — it enables journalists to better engage with readers in innovative ways.

It’s important that media houses find ways of investing in computational Journalism. That is not to say , however, that all aspiring journalists must study computer science or statistics. The key question lies in how reporters can collaborate with researchers in other disciplines to discover stories. There is need to seed new collaborations between journalists and computer and data scientists: create a bazaar for the exchange of ideas between industry/practice and academia/research.