How to create the perfect news aggregation system with mobile analytics and cognitive computing
In this digital age, it’s unsurprising that, according to the Pew Research Center, more than 57 percent of Americans get their news through one or more internet or mobile digital sources. This shift from traditional to digital platforms has allowed Americans to increase their news consumption. With an approximate 2 million articles published online daily, as reported by MarketingProfs, publishers and readers alike must consider the effectiveness of their current distribution systems and consider how mobile analytics can help.
Many people rely on aggregators to help them navigate through the myriad articles, and for each news event, readers consume different stories from different sources. What leads each reader to the news outlet he or she prefers to read and engage with? Using mobile analytics and cognitive computing, there may be an opportunity to create an aggregation system that spans beyond topic and content.
In 2006, Tania Lombrozo observed that when approaching new information, we immediately try to make sense of it by processing it through our personal context before we gauge our interest and relevance levels. Marcus Raichlea and Abraham Snyder further discovered that this base of knowledge is important and that it works instantaneously with our gaze to determine whether we continue to read and focus to actually understand the words. Given this, it makes sense that people seek stories and explanations relevant to themselves beyond mere facts.
When the same news event leads to thousands of articles, how will the best be selected? This is a question that could be answered through mobile analytics. With each unique user comes a unique data set of what, where, when and how they interact through their mobile devices. From this, the aggregation system could not only determine the depth of exposure to an event but also determine the interest level and comprehension of the reader to curate articles that better fit their needs. Mobile analytics will help select the topics and content of interest to the reader. Combined with cognitive computing, this experience could be further personalized through context.
Perspectives and context
Dr. Ziming Liu, whose research focuses on the impact of digital reading, has shown that with new technology comes new behavior, and in this case, a new reading pattern known as screen-based reading behavior. This phenomenon is characterized by more time spent on browsing and scanning versus in-depth and concentrated reading.
Most notable and alarming about this new behavior is the decreasing sustained attention. To capture this little time given, the context of each article and the reader’s linguistic preferences need to be taken into account. Does the author’s headline selection converge with the reader’s perspective? Studies by Elly Ifantidou show that headlines are translated and inferred based on each individual’s lexical adjustment processes with assumptions and interests combined to retrieve a plausible and relevant interpretation. Furthermore, in a 2008 report, Zeshu Zu claims linguistic preferences present insight into an individual’s natural rationality properties.
With mobile analytics comes a more personalized experience. Many companies are able to customize their services based on a user’s interactions with their products. Combining this with the ever-evolving cognitive computing capabilities could create the news aggregation system we’re all waiting for — something that is equivalent to personally browsing through the 92,000-plus articles each day to pick the ones most interesting and relevant to an individual reader.