OUR THINKING/ARTICLE

How data journalism can improve your content

An interview with Ioannis Antypas, Longitude’s new data journalist

Ioannis recently joined Longitude to help us serve the growing demand for alternative research techniques that can help our clients to create more engaging stories and original thought leadership campaigns.

An experienced data journalist, Ioannis joined Longitude after spending several years in Brussels working as a data journalist and correspondent for German broadcaster Deutsche Welle, and Greek newspaper Proto Thema. Before that, Ioannis completed his Fellowship in data journalism at Columbia University, New York.

 

Good morning Ioannis. A good place to start would be answering the question: What is data journalism? And how is it changing the way professionals in media and comms research their stories?

So data journalism is a very broad profession. It starts with the traditional journalist’s desire to find interesting stories and truths about the world and opens up a whole new set of tools and techniques to help us uncover new stories and insights that previously would have been difficult – or impossible – to research.

As a profession, data journalism is sometimes closer to computer science than traditional journalism. Based on exhaustive research, a data journalist can collect huge volumes of data, use coding skills to automate its manipulation and then drive insight. The most interesting human stories of our times – about the way business, the global economy and our societies are evolving – can be explored and illuminated by these new approaches research.

We’re a rich, data-driven society – and journalism needs to follow suit to remain relevant.

How does computing power boost your ability to find more interesting stories?

Data science is effectively digitising the pen and paper and changing the way in which stories are researched and constructed, but it is shifting the scale as well. Being able to scrape and construct these new datasets means that we can now scale up the process and multiply the effectiveness of what one person can do, tenfold. In simple words, with the help of computer programming, we now analyse far more data than before, allowing us to handle much bigger investigations and extract more resounding insights. Programming in journalism works in a similar fashion to other fields; It takes care of the time-consuming, repetitive process, allowing us to become exponentially more creative.

Journalists have a new toolbox. It’s a toolbox that is constantly being updated and upgraded to the extent that, with the help of democratised programming languages such as Python and JavaScript – and their enthusiastic communities of open-source programmers –  we are able to tackle just about any digital task that we put our minds to, and investigate with immeasurably more scope than previously.

How can brands apply the tools and techniques of data journalism to create better content or thought leadership?

The effect that data science could have on thought leadership is immeasurable. A huge part of thought leadership is research data, and our Learning from Leaders report proves how valuable that type of insight is to audiences.

Companies tend to default to surveys to uncover new stories and insights – and they remain a valuable tool in the armory. But there’s only so many surveys that can be published on the same topic – and there are other stories to be told that aren’t suited to that approach at all.

So we’re now offering these tools and techniques to assist brands in delivering new and original stories and real insights. This is often swifter than more traditional research and allows brands to approach complex business topics from different angles. To me, provoking those established thought leadership norms will really stand out, and is the essence of what makes a brand a ‘thought leader’.

I like to think that the data that I am able to ‘scrape’ from the web is often the truest quantitative representation of society that we can access. And that’s hugely useful when trying to interpret feelings around topics or events, an executive’s behaviour around a specific theme, or even the basic level of ‘noise’ around important subjects. Navigating this noise and gradually structuring the unstructured, is where a data journalist thrives and adds additional layers to a brand’s capacity to project true thought leadership. Content will be more relevant, more insightful, and ultimately more interesting to read.

So does data journalism spell the end for surveys?

No, not at all. The survey still has a place in thought leadership without a doubt. For projects with certain hypotheses, data science techniques may not provide the whole answer and a survey might be a better fit for what is needed.

The techniques learned from data science and data journalism are designed to augment the thought leadership process, rather than replace elements of it. Yes, data journalism will make some projects and investigations possible when before they might not have been, but the core elements of the thought leadership process will basically stay the same – just bigger, and better.

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