The emptiness of Data Journalism

Data Journalism is a new trend of storytelling. Here, traditional journalistic methods are combined with data analysis, programming, and visualization techniques to create readable and interesting news stories. Some rock stars of this new trend include The Upshot of The new York Times, DataPoint of The Sydney Morning Heralds, The Guardian and The Vox.

However, not every journalist knows how to utilize the potentials of Data Journalism.

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This is my favorite illustration! Thanks, Barry Blitt!

Every day when browsing through news on the internet, have you ever felt that, somehow, they are all the same? If journalists simply think of data journalism as a process of shuffling mountain of data and putting together a readable summary, then it’s easy to understand why we have to read hundreds of identical news every day. It’s all aggregation!

Many fans of data journalism believe that the data will show us all. And their mission is trying to answer every question using data, not anecdote. However, sometimes what the data tells us is biased rather than objective. In his article, Michael Kinsley argues that the nature of life is complicated and motives can be subtle.

If all data point to the conclusion that the earth is square, then will you say so in your article? The story of Nate Silver may make you rethink of this.

Nate Silver is one of the most famous data journalists in the US. He is also the founder of FiveThirtyEight website, which he describes as a regime of data journalism. Silver has been criticizing the value of traditional newspaper and television. And he honors only investigative journalism and data journalism. Given his data analysis, Nate Silver was down on Trump’s prospects throughout the US election. He even gave Hillary Clinton a 71.4 percent chance of beating Trump. That’s why many old-school journalists can’t wait to laugh at him after Trump’s victory.

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Talking about Silver’s failure, Timess media columnist, Jim Rutenberg concludes that “a good place to start would be to get a good night’s sleep, and then talk to some voters.”

And I totally agree with him.

Up with the facts! Down with the cult of facts!

Quantitative data should be an aid to journalistic practices, but it shouldn’t be a replacement for traditional journalistic methods. Such measurements are appropriate to some particular subjects. However, the assumption that it is appropriate to all subjects is not at all adequate. There is no numerical answer to the question of who deserve to receive food relief from the government, or whether gay marriage is acceptable. Interviews, opinion columns and all kinds of journalistic commentary need to be given equal honor to vary the voices and pave way for a free society.

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Advancing into an impeding future

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Touching down with regards to what has been discussed so far, what can we come to expect from the future of news? More specifically, the next generation platforms and content production and consumption. The ‘google glass’ project for example, was an attempt to progress into Web 3.0 where communication interaction was tailored to fit and accommodate the independent audience behaviours that seem to come more and more into their own in regards to news production and consumption.

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The internet as an open global network has changed the business of media to one that involves more emotions, power and sourcing on the audiences’ part. This empowered ability of ‘citizen journalism’ has brought about questions of credibility, quality and authority of news in kind. With google glass’s user-centred functionality and semi-isolated environment, does it empower audiences further into a corner that renders media professions obsolete?

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Traditionally, the media had the power as gatekeepers of information. Then came Web 2.0, where the media had to take a step back to the growing public control and updated their role as ‘bridges of information’. As a bridge, the media still engaged in their involvement in steering and facilitating new conversation. However, with the advent of a new web generation, will public control turn into total domination? Could the public reclaim the role as gatekeepers in a vice versa spin with the nature of news, dubbed ‘attention economics’ is transforming further to adapt to the audience rather than audience to news.

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The reliance of news on social media and online networks have also brought about A.I.-curated news, which further stress the question of how all these replacements will affect the media profession’s existence as well as the standards of news.

Presentation is everything

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Continuing on with what was discussed in the last post on ‘data journalism’, here we will take a more positive light and explore one of its facets: data visualisation. Quite literally, data visualisation deals with packaging process of all the material gleaned from data journalism. Again, bringing back what was said about the fast-paced nature of the online environment and attention spans shrinking, visuals represent one solution to that setback. Presentation is everything as audiences are able to access raw data themselves through the openness of the web.

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Data visualisation takes a page out of advertising’s book in terms of being able to translate raw black and white information into engaging graphics that catch attention mainly because it taps into an emotional level with respective audiences. The ability to engage with into audiences’ subconscious through a powerful rhetoric is a mnemonic technique instilled in data visualisation.

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The personal nature of this connection made sparks a sense of one-on-one moment in a one-to-many Web network. The advantages of graphically effective data visualisation could build up relationships and gain a loyal following from audiences with affiliated affinity. The distinction between ‘data visualisation’ and ‘data journalism’ is relevant as content quality may be faulted and compromised in some manner but graphics cannot be, in a sense that without it, chances of engagement is bleak.

Data journalism: empowering or overpowering?

With the open and interactive nature of online networks, what does it mean for the content producers of today to able to catch the shorter audience attention span in a busy and information-filled environment nowadays. Data journalism has come into play where professionals and academics alike take to this nature of a fun and light approach in engaging audience with topics of debate. The playful nature of this approach is generally meant to produce legible and engaging stories that are easily digestible for audiences.

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To an extent, data journalism is very ‘assistance-heavy’ as it relies heavily on procuring material for publishing from technological databases and crowdsourcing open audience information. The data journalism notion of ‘outsourcing’ material and packaging it to fit trending material brings about question of credibility and intentions. The lean towards quantitative rather than qualitative essence in data journalism causes concern whether standards of news/content delivery is dropping and in turn, putting audience enlightenment in decline. The aim for topical trends also questions the intent for virality rather than informational, as news is supposed to be.

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Similar to online networks in the media, data journalism is but a tool and not to be confused as the media field in itself. And as with any sort of tool, there should be a healthy dose of skepticism. In this case of data journalism and what was discussed about its goals and standards, risk looms as with any kind of content production, it has to ability to potentially shape and/or restrict readers’ minds and perspective. Being in the dangerous business of power and control always comes with responsibility as consequences, as we all know too well of…..

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Will data journalism replace traditional journalism?

This week, we move to data journalism. I am interested in the possibility of data journalism can replace traditional journalism.

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First of all, the premise of data journalism is a variety of data disclosure. If there is no data disclosure, data collection, collation and analysis cannot be conducted. However, it is not easy to get the big data, nor is it can be seen in all the areas covered by news reports. As a result, data journalism is a new form of news coverage in the era of big data, which reinforces certain areas of news reporting and makes up for the weakness of traditional news reports. Therefore, in my opinion, data journalism cannot completely replace traditional news reports but can complement traditional journalism.

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Secondly, big data in the amount of information on the advantages is easy to make people have too optimistic about the news reports base on big data. However, from the perspective of data properties and production, the fact is opposite. Firstly, it is very hard to prove the reliability of data journalism. In addition, the majority of the source of data journalism is from the government, enterprises, social groups and other public databases. Although these data provide sufficient statistical data for news reports, some valuable information is not public and even be protected as secrets. Thus, in my opinion, the data available to the media is limited. And in this case, the data analysis is likely to be inaccurate.

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Confirmation bias in data-journalism

Data journalism can simply be explained as the use of data as a tool to tell or explain a news story. It can be in a form of infographics, statistics, charts, graphs, etc.

So who are these data journalists and how to be one?

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The good news is that you don’t necessarily need to be part of a large corporate media, a developer or even a coder to be a data journalist. Although of course, working under large corporations like The Times has its own benefits in terms of having more budget and resources and having people with actual reporting experience and skill.

Even so, technically, anyone can be a data journalist. All you need is a web access and you’re settled.

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With websites like OECD Statistics, World Health Organization and UNData giving free public access to everyone, anyone can do it.

Now although everyone can do it, it is important to note that not everyone can do it well.

However, its major advantage could also be its major disadvantage. The fact that anyone can be a data-journalist could also pose as a potential threat for the society.

It is important to highlight that there is a false sense of impartiality with data journalism.  For example, have you ever purposely put in a lot of those complicated statistical, numerical data in your presentation just to make it looks more professional and credible? I know I have.

Now I’m not saying it’s wrong, we do it because many people (I’m guilty for this too) will actually fall for that trick.

They might assume that by reading all these numbers and seeing all these graphs, it must be true. Yes, the information presented might be true, but it doesn’t necessarily mean it’s not biased. As mentioned by Sarah Cohen from The New York Times, just because it’s data doesn’t mean it’s not subjective.

Like any other types of journalism, there is always a possibility of author’s bias. So instead of critically analysing the facts, consider their good and bad aspects, conclude it based on their pros and cons, and present it in a way that is unbiased, many authors engage in a confirmation bias. This happens where authors tend to search, interpret and collect the data in a way that confirms their prior beliefs.

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In short, it exists when the author wants what they believe to be true, which might lead to tainted or misleading results.

An example can be seen from one of Buzzfeed article, where they claimed that Democrats watch more porn than Republicans.

Guess where the source was from? Yup, PornHub.

So although it is a data-backed journalism, it is still an opinion journalism. So as we wade into the ocean of data journalism nowadays, let’s not forget that it is also important to be aware of what we can and cannot trust.

Network Effects – A case study of ISIS

This week, I read this great article “Why ISIS is winning in the social media war”. And I think this is a great example of the network effects and how these impact the dissemination of ideas in the digital age.

Did you know: More than 30,000 people around the world have turned their backs on everything and travel thousands of miles to Syria or Iraq, where they were told a paradise awaits? Many people seduced by ISIS’s ideology are willing to die under the Islamic State’s name.

How did ISIS magically cultivate its ghastly brand and ideology in the hearts of potential recruits who even live in the US or Europe? This is what all media professionals wish they could do with their target audience.

How the magic happens?

I was still confused about those things until I read this article and The Diffusion of Innovative Theory this week.

ISIS has been so successful in using network effects and social media to spread its idea among internet users and rouse followers that al Qaeda could never reach. ISIS has clearly targeted specific Muslim enclaves throughout the world and defined who are the ‘opinion leaders’, ‘change agent’ and ‘adopters’ within those communities. Given the understanding of how these networks operate, ISIS, then, creates varied content that caters to niche audiences and facilitates the adoption of its ideology among those groups. This is explained in this great video!

These are examples how ISIS’s message has found a foothold among people who are struggling with their own idiosyncrasy within the US society. ISIS brand has become so ubiquitous. It has transformed into something like an open platform, upon which the desperate and deluded are connected and encouraged to contribute personal narratives of persecution.

ISIS is a great case study in terms of employing network effects to influence customers’ attitudes and behaviors.

Network Visualization

Nowadays, advances in technology make it easier for us as media professionals to analyze and exploit network effects by network visualization softwares. Network visualization helps us effectively navigate thought leaders and understand customer social influence. Thus, we can identify the dissemination of news around networks of people to make fast and cost-effective decisions.

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Is there any risk using network visualization?

In a study about network analysis, McGrath and his colleagues conclude that care should be taken when using visual representations of networks. Varied graph layouts alter our judgment about the most prominent nodes within the networks, thus give us misconception about the network’s structure.

Despite all the pros and cons, I believe it’s worth for us as media professionals to explore and conquer the implementation of network visualization if we want our integrated marketing communication campaign to be as successful as ISIS’s.