Technology Journalism: Robo-Journalists

The awkward moment when you hit “Save” rather than “Publish” and so hand in a blog post late…

– Nikolày

I understand technology journalism as journalism focused on technology, but I also came across a semi-related sector of journalism I had no idea existed – and it’s too cool not to share: robo-journalists.


Now if you’re anything like me, hearing the name “robo-journlists” immediately conjures up the mental image of Robocop sitting in an editors room, slaving away over the next big scandal. While the reality isn’t as iconically awesome as that, it’s still pretty cool.

Over the last couple of years, organisations such as the Associated Press have been using automated algorithms that are able to produce earning reports that ultimately result in approximately three and a half thousand stories per financial quarter.

As of last year, Reuters has also partnered with tech company Wibbitz in order to create an algorithm that is able to automatically create digital video packages for news events as soon as pictures, information and video clips become available. While the robo-journalism technology is primarily intended to create digital video to summarise European football matches, it is planned to develop such technology to cover all sorts of news genres.

May as well throw in the towel, by the time I finish this Journalism degree, I could very well be redundant.


Data Visualisation As Art

If my last blog post about data journalism wasn’t a dead give away – I’m not a huge fan of numbers. Just the mere mention of numerical equations results in terrifying flashbacks of failing 10th Grade Algebra. So when the course outline listed two weeks worth of topics purely on data, I was less than thrilled. But turns out data visualisation is actually visually beautiful, and can have layers of meaning.

Pictured below: Not Me – It’s A Fan of Numbers, Puntastic


In 1957, Frank Lloyd Wright defined art as a discovery and development of elementary principles of nature into beautiful forms suitable for human use. Data, on the other hand, typically records information about occurring phenomena. While some may find numbers fascinating and certainly suitable for human use, I personally don’t find them subjectively beautiful as numbers on their own. Yet once the data is rendered, or presented, in a manner that is visually presentable to the numerically illiterate,

Projects like the An Examination of US Gun Murders (screenshot below) thoroughly exemplify the marriage of numerical data and beautiful visuals to create art with meaning that can then be taken away to be used by humans. Demonstrating the number of gun killings in the US, the age at which the victims died (represented by the orange parts of the lines) in comparison to the age at which they would have been expected to die due to natural causes. The piece isn’t only informative but evokes a stirring of emotions as the harsh realisation of years of life lost to senseless violence soars higher and higher on the counter on the top right of the screen.

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Full Video Here, Just Click On The Picture


Data visualization: Is a picture worth a thousand words or a wasteful effort?

“A picture is worth a thousand words.”

That’s why ‘Data Visualization‘ was born.

Actually, I’m a big fan of data visualization. Without this beautiful infographic, I will never understand how a car engine work(lol).

how-care-engine-works infographic

However, the way we are praising data visualization is somewhat pompous. It makes us completely blind to the risks of visualized data.

Data misinterpretation

In a study about graphic representations of information, Bresciani and Eppler conclude that there are three potential risks inherent in visualization:

De-focused: When creating a graphic, it can be tempting to focus more on the layout than on function. Be careful! Too many unnecessary ornaments or too many unrelated elements emphasized at the same time can distract audiences. They don’t know where to to focus, thus get completely confused about the graphic.

Disturbing: Some images can shock or upset the viewers. This echoes with the findings from Seeing Data project, a research conducted by data visualization expert Andy Kirk. Andy indicates that although the viewers tend to not exactly remember the data from the graphics, they could remember the overall impressions, and, significantly, the emotions that the graphics evoked. Therefore, designers need to pay careful attention to the emotional aspect of graphics because this can affect the way the audiences interpret data through visualizations.

Cultural and cross-cultural differences. Because of the heterogeneity of audiences, some graphic representations may be misinterpreted. For example, Western viewers tend to focus on the foreground, while east-Asian audiences focus on the whole picture and the background. Color meaning also varies in different cultures. Thus, designers need to consider cultural elements, especially when creating visualizations for cross-cultural audiences.

The rise of lazy audiences

We need to do infographics because our audiences become so lazy. Reading data is more work than their lazy brands want to do. This makes me upset thinking of infographic and all kinds of data visualizations.

Data journalist’s role is to access and present the data on the public’s behalf. However, it is public’s responsibility to analyze and draw understanding from data themselves.

If someone is interested in a specific topic, he/she will give the most effort to consume a whole load of information. If they think this kind of knowledge is too boring and useless for them, then creating an infographic to help them understand that topic is just a waste of time. What for?

We tend to think data visualization is trendy. But why we need to make that fancy animated infographic just to explain how to eat an artichoke (lol).


Again, I love data visualization. However, data visualization sometimes can make audiences confused about the content rather than making it easier for them to consume the data. Moreover, as media professionals, we need to consider carefully when data visualization should be used and how. It’s a waste of time and effort to follow the graphic trend without a clear purpose.




When to trust data visualisation (and when not to)

If you ask whether people prefer to see images rather than text to process an information, I’m pretty sure the answer would be a resounding yes. Why?

Because humans are visual creatures.

Research from 3M corporation has found that we process images 60,000 times faster than text. This might explain why we find visual data is more appealing and attractive:

simply because we can understand it quicker.


Image 1

This might also explain the increasing number of data journalism we see everywhere we go, whether it’s on TV, social media, and even newspapers. The emergence of data journalism certainly, has not been ignored by journalists or even amateur bloggers.

A staggering number of people and businesses are racing and competing against each other to make the best and most creative infographics that are appealing to the audience.

However, often, at the expense of credibility and accuracy.

As discussed in the previous blog post, there are some problems associated with infographics and data journalism. Fisher’s ‘map of the world’s most and least racially tolerant countries‘ can perhaps serve as a perfect example of how data journalism are often flawed and misleading, yet, it is blindly accepted and believed by millions of people in a heartbeat.

The fact that colours and designs have more impact on people’s perception of messages, rather than the actual credibility of the data source, says a lot about the issue of interpreting infographics.


Image 2

So how can this issue be solved?

First of all, it is important for anyone that create infographics or data visualisation to disclose where the sources associated with their data and graphic are coming from, and more importantly, how their data/work should or should not be treated as scientific fact.

And secondly, by raising public awareness about the issue of accuracy in data visualisation, to prevent the spread of fake news or misinformation.

But how do people identify inaccurate/faulty data?

John Burns Murdoch came up with this list you have to check before believing in any data visualisation. It is not anything revolutionary, it is just the kind of thing that people can do mentally and automatically in their mind when seeing a data. If the data failed to check all the lists provided, then it is probably best to not trust the data.

How to employ Data Visualization?

Visualization is a graphical representation of data descriptions that is intended to reveal the complex information in the data at a glance. Data journalism visualization is the application of visualization in the field of journalism, integrating data with news value, serving the needs of communicating news and satisfying the audience’s access to information


(Google Image)

Using visualization is able to more effectively show news value. Data can tell the truth as well as news can tell the truth, they are consistent from a perspective of news value. And data is a more intuitive form of storytelling. Through the visualization, the most of the useful data can be integrated, more effectively, more intuitively and more interestingly to attract the audience. Moreover, through the various elements of the news and events related to the integration of factors that lead to the reader’s thinking, extend the impact of news and related aspects.


(Google Image)

Well, in my opinion, data visualization is not a panacea for data presentation and cannot be blindly used. It is not advisable to visualize the data when the news story can be successfully reported in a traditional journalism way or if the data of the news story is not enough or lack of relevance.


(Google Image)

Stories in Data Journalism

Narrative is essential for context and meaning. That’s the point I’m about to try and make – let’s see how it goes.

A few weeks ago I was sitting in one of my Masters level media papers (not this one, don’t worry) where the lecturer was attempting to explain his belief that because Julien Assange created Wikileaks and enabled huge data dumps of information that he was now one of the world’s most influential journalists. The thirty or so students in the class all seemed to unanimously agree – except for me. Something didn’t feel right about the statement. Why would providing copious amounts of information to the public, void of any sort of contextual political or social narrative to explain the information, suddenly entitle someone to be called a journalist? I wouldn’t throw flour and eggs and cocoa powder at your face, tell you I made you a cake, and then proclaim myself one of the world’s most influential chefs while you sit there covered in ingredients wondering what the hell just happened and who the guy throwing food about the place was.


Then I watched a TED talk by Ben Wellington about data and stories, and immediately felt a probably overinflated sense of affirmation in my stance. In this talk, he discussed how integral it is for a journalist to attach narrative and story to data sets, otherwise people won’t care. Summarised into four short points on how to attach narrative:

1) Connect with people,

2) Try to convey one idea,

3) Keep it simple,

4) Stick to what you know best.

Without applying such an approach, data is just numbers – and not THAT many people like math.

Data journalism— Why it become so popular


To put it very simply, data journalism is journalism done with data. This is the simplest definition of data journalism I could found. But the thing confused me is that it is really necessary to tell a story by using numbers? I think I may not the only one who hate mathematics, so it is interesting to find out how to tell a story with numbers? Is number the parts of the story, or number form the whole story.

To answer these questions, we should back to the rising of data journalism, why it emerging so rapidly?

I think the first reason is that in the online age, more and more data are easily accessed by everyone as never before. The Internet breaks the geographical limitation that allows journalist to look for data and create story anywhere they want. For example, digitising public database about government spending are access to everyone, besides, leaked documents published by WikiLeaks or “big data” generated by social networks such as Google or FB is also available, the only thing need to concern is to clarify the credibility of data.


Secondly, powerful data analysis tools are available to allow us to organise data in an efficient way. Some of the powerful tools are even free or open source. You can produce powerful graphics or visualisations without having technical experience or coding knowledge. That is an important reason for a journalist to put visible numbers in their report.

It sounds wonderful to telling a story through data, but data journalism can not replace the traditional journalism, it is an addition basic skill to the journalism. Data journalism is bridging the gap between stat and news report, it gives the news practitioners new challenge to identify the trend. Even though data journalism is the future of news report, but for those who hate numbers, it is hard to adapt to it.