New Trends in Feature Writing: Science, Multimedia, and Data

Feature writing has always been about telling deeper stories – the kind that go beyond headlines and inform, engage, and linger in the reader’s mind. But the craft is not static. In today’s digital environment, three powerful trends are reshaping how feature writers approach their work: a surge in science-focused stories, a shift toward multimedia-integrated narratives, and a growing reliance on data to anchor and substantiate reporting. Together, these trends are producing a new kind of feature journalism – one that is richer, more credible, and far more accessible to a general audience.

The growth of science feature writing 🔗

For much of journalism’s history, science coverage was confined to specialist publications and academic journals. It was dense, jargon-heavy, and rarely written with the general reader in mind. That has changed substantially. Science journalism today exists to report on healthcare breakthroughs, climate change, emerging diseases, and a wide range of other developments in a way the public can genuinely understand and engage with. The demand is real – and so is the audience.

The digital age accelerated this shift. With readers able to access information from almost anywhere, publications from The Guardian to Scientific American began investing in science features that connected complex topics to everyday human experience. The COVID-19 pandemic was a defining moment. Science journalism played a critical role in helping audiences understand what was happening, when life might return to normal, and how to interpret rapidly evolving medical guidance. Writers like Ed Yong at The Atlantic, whose pandemic coverage won multiple awards, showed that covering science well requires more than understanding virology – it also requires knowing how to frame uncertainty, communicate risk, and connect to the broader social and human context.

Finding the human angle in science 🔗

The most effective science features don’t simply relay research findings. They find the human story embedded in the science. A feature about CRISPR gene-editing technology, for instance, becomes more compelling when it centres on a family living with a hereditary disease – showing why the research matters, who it might help, and what ethical questions it raises. This approach transforms abstract concepts into relatable, emotionally resonant narratives without sacrificing accuracy.

This is the core of modern science feature writing: making the unfamiliar feel urgent and relevant. As the Reuters Institute for the Study of Journalism has noted, some newsrooms are increasingly investing in specialist science and green technology coverage, recognising that audiences want informed, substantive reporting on topics like climate change, AI, and public health – not just breaking news. Features on these subjects, when done well, give readers a framework for understanding a complicated world.

The rise of multimedia-integrated features 🔗

The shift from print to digital platforms did not simply change where people read – it changed what reading means. A feature story published online is no longer just text on a screen. It can include embedded video, audio interviews, photo galleries, scroll-based animation, and interactive graphics, all woven into a single, cohesive narrative experience.

Research on multimedia journalism confirms that incorporating visual elements such as images, audio, video, and interactive components significantly enhances both user engagement and information retention. Feature articles, in particular, tend to carry higher multimedia density than standard news content – and for good reason. Features are built around depth and immersion, and multimedia elements extend the reader’s ability to engage with a story at multiple levels simultaneously.

What a multimedia feature actually looks like 🔗

A landmark example is the New York Times’ Snow Fall: The Avalanche at Tunnel Creek, which combined longform text with video, audio, and interactive graphics to reconstruct a deadly avalanche in forensic detail. Studies examining the piece found that scenes were vividly reconstructed through the interaction of text, image, video, and graphic animation – each format contributing something the others could not. The text carried the narrative; the video provided presence; the graphics explained physical processes that words alone would struggle to convey.

This kind of storytelling is no longer exclusive to major newsrooms. Advances in digital publishing tools have made multimedia production accessible to a much wider range of journalists and publications. As practitioners in the field have pointed out, a multimedia story is not simply an article with a video dropped in at the end – it is a story where every format serves the narrative, and each element is chosen because it communicates something the others cannot.

Mobile, e-papers, and the shareable feature 🔗

Smartphone optimisation has become an essential consideration in multimedia feature production. Studies from the Pew Research Center found that more than seven in ten Americans were accessing news on mobile devices just a few years into the smartphone era – a figure that has only grown since. This reality pushed newsrooms to rethink layout, typography, image sizing, and interactivity for smaller screens. Customised digital editions and e-papers have similarly adapted, prioritising readability and shareability on mobile platforms. The result is that a well-crafted multimedia feature today is also a shareable piece of content – designed to travel across platforms, reaching audiences far beyond a publication’s core readership.

The impact of data-driven journalism on features 🔗

The third major trend reshaping feature writing is the use of data – not merely as supporting detail, but as the foundation and driving force of the story itself. Data-driven journalism, as defined and extensively examined by the Tow Center for Digital Journalism at Columbia University, goes well beyond traditional journalism with more numbers. It involves journalists actively gathering, organising, analysing, and presenting large data sets to answer a core question: why is something happening, and what does the evidence show?

The critical insight from the Tow Center’s research is that data is not a neutral, self-evident resource. Data is socially constructed – it is shaped by the people who collected it, the questions they were trying to answer, and the context in which it was produced. Understanding a data set well means understanding the people and processes behind it. This perspective has pushed the best data journalists to treat data with the same critical rigour they would apply to any human source.

How data elevates a feature’s credibility 🔗

When data is integrated into a feature story, it shifts the piece from assertion to evidence. Rather than a writer claiming that housing affordability has worsened, a data-driven feature can show the reader – through interactive charts, maps, or comparative visualisations – exactly how prices have changed, in which areas, and over what period. Data visualisation tools allow journalists to present information in formats that make complex patterns instantly visible, building transparency and reader trust in ways that prose alone rarely achieves.

Landmark examples demonstrate the power of this approach. The International Consortium of Investigative Journalists’ work on the Panama Papers – a massive investigation into offshore financial dealings by powerful global figures – relied entirely on data analysis to sift through millions of documents and map a complex web of transactions. The Guardian‘s “The Counted” database, which tracked every police killing in the United States in 2015, used structured data to bring empirical rigour to a deeply charged public debate. Both projects combined data with narrative to produce features that had genuine public impact.

Transparency as a journalistic value 🔗

One of the most important principles in data-driven feature writing is transparency. Researchers and practitioners in the field argue that journalists working with data must show their work – providing links to original sources, making raw data files available where possible, and being open about methodology. This transparency serves a dual purpose: it allows readers to verify the analysis, and it helps rebuild trust in journalism at a time when that trust cannot be taken for granted.

The Tow Center’s research also warns against uncritical “data-ism” – the assumption that numbers are inherently objective or authoritative. Bad data, biased data, and flawed analysis can mislead just as easily as poor reporting. Data-driven feature writers must therefore combine technical competence with traditional journalistic scepticism, treating data as a source to be interrogated rather than an oracle to be deferred to.

Where these three trends converge 🔗

What makes this moment in feature writing particularly significant is that science, multimedia, and data are not developing independently – they are converging. A feature on climate change, for instance, might combine a data-driven foundation (satellite measurements, temperature records, emissions statistics) with multimedia elements (interactive maps showing coastal flooding projections, video testimonials from affected communities) and a science-informed narrative that explains the underlying mechanisms and human stakes. Each element reinforces the others, producing a feature that is more persuasive, more accessible, and more complete than any single approach could achieve alone.

Ongoing research into AI’s role in journalism adds another layer to this picture. As automated tools become capable of processing large data sets, generating preliminary drafts, and personalising content for different audiences, the practical boundaries of what a feature writer can produce are expanding. But the core competencies – critical thinking, narrative judgment, ethical rigour, and the ability to find the human story inside the data – remain irreducibly human skills. The trends shaping feature writing are ultimately about giving those skills better tools and wider reach.

What do you think? As science, multimedia, and data reshape feature journalism, does the emphasis on evidence and interactivity risk crowding out the more literary, voice-driven qualities that have long defined great feature writing? And should journalism schools be training future feature writers more as data analysts and multimedia producers than as storytellers?

References

1. https://shorthand.com/the-craft/science-journalism-examples/index.html
2. https://reutersinstitute.politics.ox.ac.uk/journalism-media-and-technology-trends-and-predictions-2024
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4. https://www.mdpi.com/2078-2498/9/5/123
5. https://shorthand.com/the-craft/tips-tools-guides-for-multimedia-storytellers/
6. https://datajournalism.com/read/handbook/two/training-data-journalists/the-datafication-of-journalism
7. https://medium.com/tow-center/the-art-and-science-of-data-driven-journalism-f00d0d2512c9
8. https://infogram.com/blog/data-journalism-definition-examples/
9. https://www.sciencedirect.com/science/article/pii/S2451958825002453