FAQ: Data journalism and gatekeeping

The latest frequently asked questions post comes in response to a PhD student looking at data journalism and gatekeeping. Here are the questions and my answers:

How do you think the role of journalists has changed during the 21st century, especially with the data explosion and the rise of misinformation and disinformation?

Journalists and news organisations have both been forced to adapt by the increased competition, and the changing nature of the world that we report on (i.e. the fact that it is more data-driven).

Many publishers tell me they want to give their journalists data skills because they feel that they need to ‘up their game’ in order to compete with new entrants to the sector, and to create distinctive content in an environment where celebrities, politicians, sportspeople etc. all publish direct to audiences rather than via media.

It’s also often overlooked that online publishing itself involves many story formats which are inherently data-driven (e.g. interactivity), and new commercial pressures (e.g. the drive towards user engagement) lend themselves to data formats (readers engage more with data journalism).

The rise of misinformation has also led to an increased demand for factchecking, which in turn often requires some data skills.

And it’s probably fair to say that the decline in trust in journalists has meant we feel an extra pressure to show the factual basis for what we do, which again data skills can help with.

“In this age of misinformation and disinformation, objective facts became less influential in shaping public opinion than appeals to emotion and personal belief, which challenge the role of journalism in finding the facts and reporting the truth with objectivity” — Do you think this statement reflects reality?

I don’t know if that statement reflects the reality — and I think it’s important as journalists to acknowledge what we don’t know.

We need more research into audience reception/public opinion, the role of journalism in that, and how that compares historically (which means we need to be able to compare with studies done in the past).

It’s easy to over-simplify what journalism/the public was like in the past. Journalism has always been about emotional appeal: we’ve always had human interest stories and used case studies to illustrate the factual side of reporting. We’ve always reported on outliers.

So the big question for me is to what extent editorial priorities may have changed (if at all) and why (e.g. analytics means we have a better idea what approaches get read).

Alongside that, I’m interested how journalism’s role is weakened by competing forms of information (influencers, politicians communicating directly etc). But ultimately, I don’t know. And anyone who says they do is lying to themselves, unless they’ve done some proper research on it.

It’s also worth pointing out that a counter-argument to the idea that journalism is more emotional is that journalists now have access to more information than before in order to report factually (e.g. less anecdotally) and the skillsets in the newsroom have improved (e.g. more data skills), so although some factors may lead to more “emotional appeal” journalism, others may lead in the opposite direction.

What do the processes/techniques of data journalism add to the role of journalists (who practice it) or how are they reshaping this role?

I often say that good journalism should tell us two things: why should I care? And why does this matter? Data journalism adds to or increases the ability to answer the second question.

We might have case studies that are newsworthy, but the data tells us how widespread those experiences are; how systemic.

Data journalism also makes it easier to find those case studies, by helping us find outliers or the best/worst examples in a particular field.

Data journalism techniques make it easier to do investigative journalism work: partly because it often gives us an insight into systems and systemic problems, but also because it allows us to do things at a scale that previously required more human work (for example analysing thousands of documents or millions of rows of data). Investigations are no longer the preserve of dedicated investigative journalists.

Data journalism processes also facilitate better and quicker factchecking, and again this has moved from being a dedicated role to something that is expected of most journalists.

More broadly, non-dedicated data journalists are increasingly expected to be able to work with data. This is partly because journalists have to deal with data much more than they ever did (because there is more of it, and it is used widely in all fields) but also partly because the rise of blogging and social media opened them up to criticism – and competition – that they were previously protected from: the likes of Ben Goldacre have played an important role in highlighting the poor quality of some journalism and journalists have had to up their game.

What are the main ethical questions that you face while working with data?

I wrote about some of the ethical issues in a book chapter which was serialised on my blog: most are the same ethical issues that journalism generally has to consider, such as accuracy and privacy.

Some are applied in particular ways – for example, the normative value of ‘giving a voice to the voiceless’ takes the form of ‘creating data where none existed’. And I think it’s important to consider how the availability of data can affect our editorial independence (for example we are more likely to scrutinise public bodies than private companies because more data is available).

How do you ensure that the data is objective, complete and reflects the truthfulness of the topic that you are tackling?

Data is not objective, and it is rarely complete — so it’s important to recognise that first.

Data journalists treat data like any other source: it will have its biases and its blind spots, but it can be drawn on to build a picture which helps us to better understand what is happening in the world.

That picture normally involves other sources as well, so that we understand the complexity of that picture.

So when we look at data we always consider how objective it is (objectivity is always an aspiration — it is important to try to achieve it, but also important to acknowledge to what extent we succeed in that).

That includes factors like what information was collected (and what was not), who collected it and why (what biases might they have, what motivations), and how it was collected – for example what questions were asked, of whom, when, where.

What is the level of importance of the data verification step in the data journalism process?

We will look to see if we can find other sources of the same or similar information — it might be collected by different organisations or individuals with different motivations or methods. We will look at how they compare, and whether they tell similar stories.

We will look at the cleanliness of the data – that includes things like looking for outliers that might be wrong, it might be misspellings or inconsistent spellings, correcting data formats or making sure they’re consistent, changing categories or boundaries, and so on.

Finally, once we have identified what our story is about, we will check those particular details. For example, if the data says one police force has the most unsolved crime, we will approach that force and ask them why this appears to be the case.

They might reply saying that the analysis is wrong, in which case we ask them to explain why they think that. In some cases this might merely be an attempt to ‘spin’ the data a particular way, or to mislead the journalist and put them off the trail, so it is important to not take their word for that, and to check what they say.

In some cases we may find that they are correct and a mistake was made. In some cases they will realise that the published data was incorrect, in which case it becomes a story about that — and the fact that they (should now) have to correct it, and what decisions were made based on the wrong data.

In your opinion, are the techniques of data journalism making the journalists play the role of gatekeepers again — and how?

I don’t think journalists ever stopped being gatekeepers. They have become less powerful as gatekeepers, certainly, now that most sources can access audiences directly. But many sources cannot access the same audiences, at the same scale, or in the same contexts.

Many publishers have reached for data journalism as one way to reestablish their authority in the context of such competition.

In some cases this makes them the sole gatekeeper (where only they have the data) but in many they are just one source of that data. It’s worth acknowledging that organisations like the Office for National Statistics now employ their own data journalists to tell stories about their data, for example.

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