In the era of fake news, journalism should be treated as a science

28 Mar 2018

Dr Bahareh Heravi, assistant professor at UCD’s School of Information and Communication Studies. Image: UCD

As it becomes harder and harder to discern fake news from reality, Dr Bahareh Heravi from UCD is using her leading data journalism research to create effective tools for journalists worldwide.

There’s no denying at this stage that journalism as we’ve known it is gone, and in its place is a job that puts immense pressure on the journalist to produce content at a much faster pace, as it competes with social media.

This can, in many instances, lead to a journalist attributing news to a source that has purposefully gone out of its way to distort reality, leading to the rise in so-called fake news.

To that end, Dr Bahareh Heravi, assistant professor at University College Dublin’s (UCD) School of Information and Communication Studies, is leading research into data journalism to get hard facts to journalists instantly.

Prior to joining UCD, she was a research fellow and a research group leader at the Insight Centre for Data Analytics at NUI Galway, where she founded the Insight News Lab research group and led a number of R&D projects in the news and media area, in collaboration with industry partners such as RTÉ.

She also co-founded a successful software development company with university friends when she was 19 and sold her shares nearly 10 years later in 2010.

What inspired you to become a researcher?

I am inherently interested in asking questions, investigating, finding solutions and creating things.

I also enjoy bringing together small groups of people and networks to work on problems associated with the questions that come to mind.

My interest in academic research started while I was completing my master’s programme. As part of our research thesis, we needed to conduct original research not too far away from what you would do for a PhD here in Ireland, just at a smaller scale.

During that time, I was working on grid computing and interoperability standards. For this, I started working with an international standardisation group, OASIS, and I found the international collaboration and research fascinating and fulfilling.

I would say, however, that academic research is not the only way to do research. In fact, I am less interested in only academic research, and always like to have industry close and preferably involved in my research.

For me, immediate impact, even if it is small, is more fulfilling and more exciting.

Can you tell us about the research you’re currently working on?

My primary research area is currently focused on the use of data analytics, computational methods and social science methods in journalism, reporting and storytelling.

Specifically speaking, I am interested in the topic of data and computational journalism and, as part of my current research, I study state-of-the-art data journalism across the world.

Additionally, I work on information design and the best methods of visual representation of information for public consumption and reuse.

In my day-to-day work, I am often exploring how data and statistical analysis tools and techniques – as well as computational methods and algorithms – could be best designed and put in a workflow to help journalists in investigative work.

In your opinion, why is your research important?

Mass communication is a primary channel to inform the public, as well as forming public opinion, for better or worse.

This means that what journalists produce has a direct impact on our lives and on our societies. We can only hope that they are accurate, reliable and have a sharp reflection of the truth, which could be consumed and understood by the public.

As I briefly mentioned in a recent TEDxUCD talk entitled ‘How is data journalism changing the newsroom?’, my research work takes a scientific approach to journalism, and I believe that journalism should be treated and practiced as if it was a science.

Data journalism could enhance journalism and news in many ways and on various topics from politics, crime and elections, to health, and human and women’s rights.

It has the potential to help us move away from fake news towards verifiable, reliable news rooted in facts. It allows us to move from opaque to transparent.

Data journalism helps keep us, the public, informed better than ever before, and keep our governments into account tighter than ever before.

What commercial applications do you foresee for your research?

Newsrooms these days are under extreme financial pressure, and this is where they can get help from data and computational methods in their workflows.

A journalist’s secret weapon for creating great stories has traditionally been their sources. A good journalist has a list of sources that they can contact to ask questions about certain events, confirm figures or comment on them in an interview.

That is costly. Data is now a vast, mostly fresh source that, in many cases, could be accessed freely or at low costs. It is still about the sources, but they are enhanced. Using this data, you no longer need to know someone who knows someone in the ministry of transport to ask about the latest road accident figures or patterns over the past years.

Additionally, automated and semi-automated newsroom tools for various tasks such as story finding, lead finding, eyewitness finding, verification, visualisation, analysis etc are all potential commercial applications of my research and work in this area generally.

Having said that, the societal benefits to having an informed society and a democratic and responsible government is of greater value to me personally than the direct commercial revenues.

What are some of the biggest challenges you face as a researcher in your field?

Journalists are often very busy and consumed with their day-to-day activities, production schedule and deadlines. This means they often find it hard to find spare time for research-led activities, or even to learn about new tools and techniques.

It’s the same with financially stretched news organisations that do not have the extra budget to spend on training, research and development.

These activities could eventually save them time and money in the future, as well as putting them ahead of the curve in their competition with other organisations – but tomorrow’s headlines and deadlines are always the priority.

Another related challenge is that, despite the advancements in many computational algorithms and techniques, they either only work well in the labs or need an extensive lead time and expertise to train the algorithms. They are also too complicated or time-consuming for journalists to put in use.

Journalists are not, and should not need to be, data scientists and computer programmers.

This makes the application of many very useful algorithms and new tools rather complicated and impractical in newsroom settings. For many journalists and many newsrooms, something either works or it doesn’t. And if it doesn’t, you may never get another shot to get your next version tested.

Are you a PhD researcher? Can you explain your work in three minutes of engaging chat? Then you could be our next Researchfest champion. Find out how to apply here.