Biased but Balanced – honesty in the media

Is true honesty the price of democratic representation?

This claim was made in 2012 by the Columbia Journalism Review in an article which discussed the necessity for presidential candidates to “adjust their positions over their careers for political reasons.”

During the 2012 presidential elections for the USA, a controversy arose when incumbent president Obama appeared to come out in favour of gay marriage. Which is to say, the president himself was “struggling with the issue” while his vice president came out in favour. Previously, Obama had always opposed the issue. However, back in 2004 he had in fact indicated that he was in favour when he was a candidate for the state senate in Illinois.

The Columbia Journalism Review criticizes the media for framing Obama as someone who ‘evolves’ while referring to his opposing candidate Romney as ‘flip-flopping’. Romney had changed his position numerous times during his years in government and later as a presidential candidate in 2008 and 2012. Clearly, both men changed their tunes when the electorate changed in order to win over voters. The conclusion of the CJR was that politicians simply could not be honest all the time and this was the price to pay in a democracy.

Now maybe it’s just me, but I certainly hope that’s not the only reason why politicians ‘evolve’. When I vote for someone to lead my country, I expect them to be able to change their mind when they become aware of new evidence or developments. The ability to adapt is what has kept our species alive. It would be a truly frightening world if we expected our leaders to have their opinions set in stone and refused to consider alternatives.

Unfortunately, this attitude is reflected in Dutch media as well. For years I’ve read comments in the right-wing media about the Dutch Labour Party (PvdA) as the “Dutch Immigrant Party” due to its relaxed stance on immigrant integration. To the point that – according to the right-wing media – Labour seemed to forsake its own social-democratic heritage. However, lately the party has become more strict in this regard and two weeks ago this lead to two members of parlement leaving the party. Imagine my surprise when those same right-wing media published articles criticizing Labour’s party leaders for either betraying their own voters (Jalta) or for being hypocrites by changing their stance (Elsevier by means of Blendle). Shouldn’t they have applauded Labour for standing up to its own principles?

Of course, my surprise wore off when I thought of these incidents in the context of framing and media basis.

Framing

According to Entman, framing is.. “selecting and highlighting some facets of events or issues and making connections among them so as to promote a particular interpretation, evaluation, and/or solution” (Entman, 2004, p. 5). This is often done to highlight the interests of elites (Entman, 2004, p. 5).”

Jalta and Elsevier are right-wing media operations which cater to a right-wing audience. Even as they attempt to  objectively describe developments that they have historically been arguing for, they will frame it in such a manner that their readers will not consider voting or supporting Labour in the next election.

Bias

Everyone is biased. Full disclosure: I’ve spent a year tutoring immigrant children in the ‘Schilderswijk’ in the Hague. Those children gave up their free time in order to gain a better grasp of the Dutch language and school system. It was very rewarding for all involved since their grades and thus chances of getting into good schools improved. However, as a result I am slightly biased both against immigrants who’re not willing to make that effort and against native Dutch speakers who complain about immigrants but don’t give up their free time helping them integrate. I thus support Labour’s attempts to further integration. There is thus a very good chance that in judging the articles mentioned above, I suffer from the hostile media effect. 

“The hostile media effect states that supporters of both sides will consider an objective story which details the struggle as biased against them.” – H. van der Kaa (Journalistic DatA Analysis course, 2014)

Are media biased?

If you ask the question this broad, according to Dave D’Alessio in his book ‘Media Bias in Presidential Election Coverage, 1948 – 2008′, the answer is bound to be “Yes”. Journalists, editors, publishers, and audiences all have their own biases. However, those actually cancel each other out… both within and across mediums.

Journalists tend to be more progressive, while publishers tend to be more conservative. However, both tend to be careful to suppress their preferences in order to live up to the ideal of journalistic objectivity. In the end however, newspapers and other media cooperations will only survive if they manage to sell their product to the audience and thus it is the audience which has the final say.

Is the audience biased? 

Most certainly so…  but because there are so many different audiences, there are so many different media. Which is why D’Alessio’s meta-analysis of 60 years of presidential coverage showed that The media is well balanced.

So where does this leave us?

“It is as important to know how people reason incorrectly as it is to know how they reason correctly. Once we understand that, it is possible that we can learn to teach people to reason correctly and accurately.” – Dave D’Alessio

Accept that you are a biased person, accept that your audience is biased… but also accept that both you and your audience crave for news to be both educational and informative and thus as objective as possible. Do not just read the articles, comments and books you happen to agree with. Read the ones that you firmly disagree with. Try to come up with arguments both against and in favor of your own views. Engage with your audience… both your supporters and detractors. You will evolve, your audience will evolve, and so will your political representatives. It is a fact of life, and your work will be all the better for it.

Articles:

De ontsluiering van de Partij van de Arbeid – Syp Wynia (2014)

Lodewijk Asscher en de gerecyclede onschuld van de Partij van de Arbeid – Joshua Livestro (2014)

Media Bias in Presidential Election Coverage, 1948 – 2008 – Dave D’Alessio (2012)

Obama ‘evolves,’ Romney ‘flip-flops’ – Brendan Nyhan (2012)

N.B. Full disclosure: Dave D’Alessio is a friend of mine, and I’ve really wanted to use his book in a blog.:)

Modeling the real world ain’t easy

“Illustrations and graphics should be as smarts as the worlds in the newspaper.” (Edward Tufte)

When I tell people my thesis is about the evolution of morality they usually blink. Some ask for clarification, others joke, and most are eager to engage in a philosophical discussion. But absolutely no one assumes I’m basing my experiments on real people.

Data journalists aren’t so fortunate however. They report current events, and as such any piece of visualization they use has to represent the truth. Virtually no one realizes that a representation of the world is just that… a representation. It is just as much a model of the world as the one I use to test an obscure theory. But the context of journalism changes the audience’s perception, and thus their expectations. A good data journalist is aware of these expectations and keeps them in mind when choosing which visuals to accompany her story.

In his lecture on the main principles of datavisualization, Alberto Cairo gives two definitions for visualizations:
1. A graphical representation of evidence.
2. A tool for analysis, communication, and understanding.

Both stress the fact that visualizations are tools, to be used to better explain the data than mere words are capable of. It is a wonderful tool for sure, one with the potential to reach out across language barriers and show audience a pattern they otherwise might never have been aware of. However, like any tool, it should be treated with care and respect.

“Charts, graphs, maps, and diagrams don’t lie. People who design graphics do.” (Alberto Cairo)

It is very easy to tell a completely different story using the exact same data but two different graphs. Below is an example from Frankwatching.com… which graph  shows the greatest increase?

whichoneishighest

The answer is of course, neither… but because the right one’s Y-axe starts at 48%, the impression is given that the data to the right is far more volatile.

When you look at these graphs side by side in the context in this blog, the difference is easy to pick up. But as I have mentioned in previous blogs… usually the audience doesn’t have the time or energy to study these things in detail.  And those that do have the time, tend to notice these things and publish them. It is therefore the journalist’s responsibility to ensure that graphs and other forms of visualization are always correct. Not only to protect one’s audience from drawing the wrong conclusion, but also to protect your reputation as a journalist.Fortunately, there are many tips out there on how to avoid these mishaps.

“Three rules to keep in mind (when choosing your graphics form)” (Alberto Cairo)

  1. Think about the audience and the publication.
  2. Think of the questions your graphic should help answer.
  3. Can you understand the graphic without reading every single number?

Think about the audience and the publication.

If you are a data journalist, chances are that your audience is highly interested in data processing, visualizations and the subject matter itself. As such, they will notice when you present a misleading visualization and they won’t be shy to tell others about it. Do not insult your audience. 

Think of the questions your graphic should help answer.

What will your audience do with this information? Will they share it with others? Will they try to see if it matches their own data on the subject? Or will they simply glance at it and either accept or reject it, based on their existing world views? And is that what you would want them to do with it? Cairo’s advice is to make a list of these questions and use that as a guideline to decide which graph to use. The Graphic Cheat Sheet is a great help for that.

Can you understand the graphic without reading every single number?

The right graph in the example above clearly fails this last test, as it can only be read correctly if the reader looks at the numbers. Of course, exposition is at times necessary, but it’s best to put that part in words, either in the main text or as an explanation near the graph itself. An example was made during this week’s class presentations, when mapping a warzone area turned out to be very difficult due to the constantly changing situation. It was therefore suggested that readers be told that this map was made at a given time at a given date, and would be frequently updated. Personally, I agree with that idea… better to acknowledge your limits than to pretend and be caught.

Do not insult your audience, they know your world ain’t real.

They say the first step in recovery is accepting you have a problem. Data journalists need to accept that visualizations have a big problem: they are open to abuse. It is therefore important to accept that whenever you attempt to visualize your data, you ask Cairo’s three questions and use the cheat sheet to choose the appropriate format. And when you come across any limits to your chosen form… acknowledge them openly on your site, so that they themselves may become aware of these limitations. Who knows, one of them might come up with a solution.

The Path to Hell is Paved with Poor Assumptions

Validating data may cost time, but refraining from it will cost more.

How wonderful is the life of a data journalist. There is so much data publicly available that whenever you whenever you are in need of a story, all you need to do is go to an interesting data repository and start questioning it and low and behold… you have a story. Now all you need to do is write it down in clear, readable prose and maybe throw in some exciting visuals and you’ve got something truly exciting that will surely get people talking.

Take this story at fivethirtyeight.com for example: “Mapping Kidnappings in Nigeria“. This story was published shortly after Boko Haram kidnapped over 300 schoolgirls that started the international “Bring back our girls” campaign. It features a nifty interactive map that shows how the number of kidnappings rose rapidly in the past decade. Naturally it created a lot of buzz on social media…

comments

As I am sure you will agree, this is not exactly the kind of publicity any journalism organization would want, but fivethirtyeight.com is actually an organization that prides itself on being dedicated to journalism. Its foundational manifesto specifically states “… one of our roles will be to critique incautious uses of statistics when they arise elsewhere in news coverage.” As commendable a goal that is, it does give the impression that they would then think twice before publishing a story that refers to ‘media reports’ as ‘discrete events’.

I admit I do not know the precise number of articles devoted to the murders of presidents Lincoln and Kennedy, but when I typed in the phrase “president of the united states murdered” at Google, it yielded “about 41,700,000 results”. If we were to take all of those as discrete events, we’d all sincerely believe that being the president of the United States is the deadliest job in the world.

Yes, this veers into the ridiculous, but this is a ridiculous mistake to make, especially for an experienced data journalism organization.

In all fairness to fivethirtyeight.com however, they did live up to one of the hallmarks of good journalism, namely that of transparency. Rather than pull the article, they owned up to their mistake. The article is still available, but now it starts with an admission of guilt, followed by an apology and a long explanation of the many errors made.

editorsnote

So how come this mistake was made in the first place? Unfortunately, the editors did not explain that. However, the comments that I have read seem to agree on two things:

  1. “Poor proxy variables”.
  2. “Data has no meaning without context.”

Proxy Variables

The blog ‘Adventures in Statistics’ defines proxy variable as “… an easily measurable variable that is used in place of a variable that cannot be measured or is difficult to measure.” In this instance, the journalist relied on news reports about kidnappings since she could not do so on official police reports. Unfortunately for her, and her editors, she forgot that, paraphrasing Erin Simpson, “All trend analyzing using < a news article database> has to take into account the exponential increase in news stories which generate the data.”

In other words… if you’re using proxy variables, think carefully whether they really are applicable. In fact, it is probably best to check with both a statistician and an expert in the field you are covering. This will take time, but validating the data is a data journalist’s first responsibility.

Data without context is meaningless.

The original criticism by Erin Simpson actually provided some good questions. Had they been asked, answered and used in the original analysis, they would have yielded quite an interesting, and validated, story.

  1. “Total number of stories coded for Nigeria over time (what is the shape of that curve)?”
  2. “What are the total number of events generated for Nigeria over time? (What is the shape of that curve?)”
  3. “How does the number of kidnappings compare to the number of coded events? Same shape? Key differences?”
  4. “How many overall events are coded with a specific geolocation? How many get coded to a centroid? (And where is the centroid?)”
  5. “How many kidnapping events are coded with a specific geolocation? Does that change over time?”
  6. “How does this information track with other open source reporting? HRW, UN, WB local NGO crime reporting? Can we corroborate trends?”

So why didn’t they take the time to ask these questions? Data visualization expert Alberto Cairo offers several suggestions for data journalism organizations to help them prevent making these costly mistakes. In my humble opinion, they all apply to this case.

“Data and explanatory journalism cannot be done on the cheap.”

Traditionally, data journalists worked in large news organizations with an excellent network and many resources. Organizations like thirtyfiveeight.com lack those and would thus struggle to find the required expertise in time before publication.

“Data and explanatory journalism cannot be produced in a rush.”

This was likely the most crucial element in this example. In an environment which needs stories to be produced daily, journalists may well not have the time to stop, think, and verify that the way they have questioned their data set is actually valid.

“Part of your audience knows more than you do.”

Of course, that has always been the case since journalists are not expected to be lawyers, engineers, or physicians. However, the combination of journalistic transparency and public data means readers can verify your conclusions and if they find fault with it, let you (and the world) know. It is an additional risk that data journalism organizations need to take into incorporate into their work processes and business models.

“Data journalists cannot survive in a cocoon.”

As professor Paul Bradshaw mentioned in his lecture on “Setting Up ‘Data Newswires'”, the accuracy of the data needs to be checked by asking the following four questions:

  1. Who collected the data?
  2. When did they collect it?
  3. How did they collect it?
  4. Find another source of the same sort of data for comparison.

In other words, the data journalist needs to either know the domain herself or work with someone who does. This actually could work out well for the organization in combination with the previous suggestion. By reaching out to devote audience members whom you have reason to suspect are experts, one can both increase audience satisfaction and the verify the validity of one’s data.

What about time?

In data journalism, you cannot afford a hidden trade-off between time and validity. Once you have gathered a dataset for a story, you always need to take the time to validate your data and make sure you ask the right questions. Not doing so can have disastrous consequences that will make people question the value of your organization.

One potential solution for this problem is to make your audience part of the process. Turn the story into a series that is updated regularly. Start with an introduction which explains what the data set and what the question you want to see answered is. Then invite audience members to collaborate with you. If they don’t have the knowledge themselves, they might know someone who does.

Of course, this does require another process of verification: whether these experts are indeed who they claim to be. However, over time you will build up a network of reliable experts you can count on.  Better to have them assist before, than criticize your story after publication.

If Data journalism cannot afford a hidden trade-off between time and validity, then it is best to be open about it and get people to keep coming back to you.


Sources:

Bradshaw, Paul (2014). “Setting up ‘Data Newswires'”.

Cairo, Alberto (july 09, 2014). “Data journalism needs to up its own standards”.

Chalabi, Mona (may 13, 2014). “Mapping kidnappings in Nigeria” 

Frost, Jim (september 22, 2011) “Proxy Variables: The Good Twin of Confounding Variables”.

Simpson, Erin (may 13, 2014). “If a data point has no context, does it have any meaning?”

The Functional Art (may 13, 2014). “When plotting data, ask yourself: Compared to what, to whom, to where, and to when?”

When Worlds Collide in Journalism

The need for fact checking in journalism only grows as we become more aware of the world around us.

We live in the middle world, at least according to Richard Dawkins. Our brains have evolved to make sense of our direct environment and cannot fathom the rules of the cosmos or the microscopic. That’s what makes big data so fascinating, because it reveals patterns that challenge our intuition. We may be able to explain parts of it, but the entire picture? That is far too complex for us to understand, let alone explain.

That was the message I took home with me last Tuesday after attending the SAP big data college tour in Eindhoven. I’m fairly sure that wasn’t their main point – the benefits of working for SAP were mentioned a couple of times – but it nevertheless made the biggest impression. And it got me thinking as to how this applies to journalism.

We live in the middle world, but ours is not the same as that of our ancestors. In her critic of Miller’s article Kindness, Fidelity and other Sexually Selected Virtues Catherine Driscoll states that she finds it difficult to believe that a sense of ethics could evolve as a sexual signal because we all know how suitors may lie in order to present a false picture of themselves. Miller replied that our distant ancestors lived in small, isolated tribes, which made hiding your true self quite challenging. The critic thus was judging what happened in the past with her own mindset and was completely unaware of this.

Our own parents grew up in a world recovering from a world war, a world without home computers, but also a world in which news played an important role in everybody’s lives. Journalism became a force to be reckoned with in the 20th century and reliable news agencies and journalists were greatly respected. Nevertheless, if you visit you parents this weekend and ask for newspaper clippings from their childhood, you’ll likely be disappointed by the ‘mundane’ reporting. Journalists, and parents, are a product of their world and what they considered important and appropriate news may not be what journalists and young adults in our world believe it to be.

This does not make our parents small-minded, nor does it make us broad-minded, much as we’d like to think so. Generally speaking, we have become more aware of the world beyond our borders and how international developments may influence our own lives and vice versa. But we grew up in a world where globalisation has become the norm.

Note how I keep using the term ‘world’ here, not ‘time’. Different though they might be, our world is much more similar to our parents’ than to that of a poor farmer in Niger who risked his life trying to get to Europe last year. His story is told in the German periodical der Spiegel (the article is in English), and I highly recommend you check it out. It is a beautifully written description of a world completely different from our own, but which nevertheless interacts with ours in ways that we are mostly unaware of.

According to the Columbia journalism review, der Spiegel is “home to what is most likely the world’s largest fact checking operation.” Back in 2010, it had 80 fulltime positions for fact-checkers, most of which were consulted during or even before writers started on their articles. And when you see the type of articles that are presented here, you can understand why. The story blends vivid witness accounts with dry facts in a way that both moves and educates the reader. Without facts, a sceptic would write it off as a sob story, and without the witness accounts, particularly the last line, it wouldn’t have the same punch.

In Chapter 2 of the Verification Handbook, Verification Fundamentals: Rules to Live By, Steve Buttry states that journalists need to ask two questions when verifying stories:

  • How do they know that?
  • How else do they know that?

These days, people will often point to sources on the Internet to answer these questions. Which is why a good journalist tries to locate the original source, as detailed by Claire Wardle in her chapter Verifying User-Generated Content, also in the Verification Handbook. According to her, there are four elements to check and confirm content:

  • Provenance: Is this the original piece of content?
  • Source: Who uploaded the content?
  • Date: When was the content created?
  • Location: Where was the content created?

Personally, I believe another element needs to be examined as well:

  • Why do people check out this content?

Journalists are paid to take the time to examine the four elements, but ordinary people will often quote, link, or share a site because of the trust they (or their peers) put in it. And the reason for their trust is likely due to their world view, even if they themselves are unaware of this. Journalists however do need to be more aware of this, and try and explain this to their own audience.

The world has become more complex, for journalists as well as their audience. Before journalists ‘just’ needed to be experts in fact checking, interviews, and investigations. Now they are faced not only with much more data than in earlier decades, but they need to be aware of the meta-data as well and share this with their audience. An audience that is frequently too unwilling to accept that the big world they now live in, is in fact made up of a network of small, interconnected worlds.

 

Sources:

  • Buttry, Steve (2014). “Verification Fundamentals: Rules to Live By”. Verification Handbook.
  • Driscoll, Catherine (2007). “Why Moral Virtues are Probably not Sexual Adaptations”. Moral Psychology volume 1 The evolution of Morality: Adaptations and Innateness.
  • Hage, Willem van (November 4 2014). Big Data College Tour at Eindhoven.
  • Miller, Geoffrey (2007). “Kindness, Fidelity and other Sexually Selected Virtues”. Moral Psychology volume 1 The evolution of Morality: Adaptations and Innateness.
  • Goos, Hauke; Riedmann Bernhard (October 21, 2014). “Death in the Sahara: An Ill-Fated Attempt to Reach Fortress Europe”. Der Spiegel.
  • Silverman, Craig (April 9, 2010). “Inside the World’s Largest Fact Checking Operation”. Columbia Journalism Review.
  • Wardle, Claire (2014). “Verifying User-Generated Content”. Verification Handbook.