A stepping stone to personalized news: Modular journalism
News apps, websites, and social media all offer some sort of algorithmic-driven sorting of articles and content, often tweaked to meet the user’s expectations and existing profile to ensure the highest engagement possible. What if publishers did not limit themselves to altering the order of news stories but would find a way to efficiently customize each story to answer individual user needs?
This vision is at the heart of modular journalism, a concept launched by the London School of Economics’ JournalismAI. The modular journalism project’s goal was to develop new storytelling formats that reach underserved audiences. Modular journalism achieves this by reimagining the traditional news article as a collection of distinct, standalone modules. These modules can be reconfigured to create multiple storylines tailored to diverse audience segments, enabling granular customization of news stories to meet individual reader profiles.
Treating news stories as adaptable, modular entities allows for the detailed tailoring of content. For instance, a finance professional could receive articles that delve deeper into market trends without spending time on basic concepts. Conversely, a novice investor might be introduced to stories that start with the fundamentals, gradually building up to more advanced information. This method enhances reader engagement by providing content relevant to various interests and knowledge levels.
As Shirish Kulkarni, one of the contributors to the modular journalism project, explores, modular journalism presents a novel avenue for news personalization, fostering increased engagement and loyalty among readers. This approach allows for stories to be tailored to diverse audience segments, potentially broadening the reach of news outlets.
A key drawback of modular journalism is the manpower required to write and assemble different versions of the same article for different audiences. AI’s advancements in recent years have played a crucial role here, potentially leveraging user data to tailor content precisely, promising a highly personalized news experience. AI can sift through user behaviours and preferences to curate stories that answer user needs at a group or individual level. Whether a novice exploring a subject’s fundamentals or an expert seeking in-depth analysis, AI ensures content is appropriately drafted. This concept is implemented by Francesco Marconi’s idea of fractal stories, which will be explored in the next section.
Taking modular journalism one step further with fractal stories
Francesco Marconi, a computational journalist and co-founder of Applied XL, introduced the concept of fractal stories, a novel method for personalizing news content. This strategy, in some ways akin to modular journalism, segments news into independent units, or “news atoms,” each designed to be fully understood on its own. This format lets readers directly engage with any story section without missing the overall context.
In the pharmaceutical industry, where daily updates on clinical trials can be overwhelming, traditional methods of digesting this information can be inefficient. Fractal stories address this by utilizing AI to dynamically filter and update news content, focusing on the most crucial information for professionals and investors.
The approach taken by Marconi’s AppliedXL emphasizes not just the automation of news updates but also the accuracy of the content. The model ensures stories remain up-to-date and reliable through the constant analysis of vast amounts of data from various trusted sources. This system still incorporates human oversight to maintain the accuracy of the information and avoid potential errors.
Fractal stories offer a more structured and clear way to navigate complex topics like life sciences, making it easier for readers to access and understand information relevant to their interests and background knowledge. This method supports a more customized news experience than traditional journalism, catering to the growing demand for news content that is informative and relevant. At the same time, it is a potential step forward from modular journalism as AI would assist and reduce much of the work required to draft and assemble articles for many different audiences.
Axios’ Smart Brevity: addressing several user needs
Another storytelling approach that attempts to connect with modern readers is Axios’ Smart Brevity. This methodology presents complex stories in straightforward, bite-sized pieces that capture the essence of the narrative without overwhelming the reader. It’s a meticulously designed technique to cut through the noise, delivering clarity, accuracy, and conciseness in a world where many suffer from reader fatigue.
Smart Brevity hinges on the principle that every word counts. Each article is crafted to convey the most crucial elements of a story—what happened, why it matters, and what’s next—in a streamlined format that can be quickly absorbed. This approach maintains the depth of reporting while enhancing its accessibility and impact. This way, Axios ensures that readers are informed and engaged, capable of grasping the significance of news at a glance and encouraged to explore topics further at their own pace. Smart Brevity, like modular journalism, addresses several user needs. In an era where time is a precious commodity, readers appreciate content that respects their schedule.
Limitations of module-based storytelling techniques and potential solutions
Novel storytelling techniques like modular journalism, fractal stories and Smart Brevity present strengths and advantages over traditional journalism. However, they also have several challenges that publishers need to address before using them.
Resource Intensiveness and Complexity: Creating modular journalism articles and fractal stories requires significant resources to produce varied story versions and maintain complex distribution systems. To address these challenges, a hybrid content creation model that combines AI with human journalism can streamline processes, reducing the need for extensive manpower. Further, adopting scalable, modular technology platforms can mitigate costs and technical barriers, facilitating smoother adaptation to innovative storytelling formats.
Information overload: While enriching, the detailed granularity offered by fractal stories risks overwhelming readers with too much information. Implementing adaptive user interfaces and machine learning algorithms can tailor content depth, providing summaries and key takeaways to help readers avoid overload.
AI accuracy, bias and oversimplification: The reliance on AI for content curation introduces concerns about accuracy and bias, while the conciseness aimed for in Smart Brevity risks oversimplifying complex topics. Regular audits, bias checks, and collaboration with external experts can uphold journalistic standards and ensure high-quality content. Pairing concise articles with links to in-depth content and using visual storytelling can convey complexity without oversimplification.
Answering different audiences’ needs: Addressing variability in reader background knowledge and the effectiveness of content requires flexible content strategies. Dynamic content adjustment can cater to varying knowledge levels, offering educational snippets for quick explanations. Moreover, developing adaptable content templates and utilizing reader feedback can refine storytelling techniques, ensuring content resonates across diverse topics and audience segments.
