How Data Science is Shifting the World of Publishing
By Christine Yan
Data science is everywhere; I learn about it in class, I read it on the news, and I experience it while surfing the web. But how does data science intersect with writing and publishing?
Data science is increasingly becoming present all around us. Whether as a determining factor behind which ads we see as we scroll on the internet or the method of recognizing consumer patterns, data is the powerhouse behind many of our most commonly used platforms and services. Data science combines the disciplines of computer science, mathematics, and industry expertise. By utilizing scientific processes and algorithms to draw conclusions and insights from both raw and clean data, data scientists and analysts are able to apply actionable insights in ways that would improve larger organizations. However, this type of technology is not meant to solely be used by experts. Rather, the role of data science is revealed in essentially every aspect of our daily life. Consequently, there is a responsibility and necessity to translate these results into comprehensible information for a broader audience.
Data analysis generally starts with a good question—oftentimes one that is responding to a real-world problem or situation faced by an institution. This goes to show how data science does not exist in a vacuum. In fact, this field is particularly emerging in the publishing industry. Given the current trajectory of technology growth and behavioral economics, reading and writing mediums have shifted toward a more online presence, with e-books and even online retail. As a business student undergraduate with passions in data science and writing, I spoke with Jenny, a data analyst at HarperCollins, to get a fuller picture of how these two fields intersect.
From our conversation, I first learned that HarperCollins’ data science team is a relatively new initiative, one that was started right before the COVID-19 pandemic. Though small, this team quickly employed technology tools—such as machine learning, artificial intelligence, and modeling—to categorize key performance indicators for particular genres, authors, and themes. Whether tasked with cleaning and sorting the data or forming patterns from the information, each and every part of the process from turning data into actionable conclusions is undoubtedly significant.
Yet, given that data science and technology are highly quantitative, there have been questions raised regarding their qualitative and ethical effectiveness. However, through speaking with Jenny, I learned something fascinating that I believe other publishing houses and institutions across various industries can adopt from HarperCollins. One way HarperCollins accomplishes its DEI efforts is through utilizing one of its employee resource groups, known as the Book Committee of which Jenny is an active member. Each book club participant voices their thoughts on which book(s) they want to push. This then has a tangible effect on HarperCollins readers, as the book is promoted on online platforms such as Amazon, and further monitored through data analysis for its engagement. Proper representation and recognition of diverse voices and perspectives bring tremendous value to society; it influences the way current and coming generations think and understand both the world and each other.
With such large growth potential being paired with the increasing reliance on useful data for better decision-making, data science is clearly crucial to a smooth transition between Web 2.0 and Web 3.0. However, with this transition, no one should be left behind. This is particularly important because this change in technology has the potential to offer economic mobility for many different groups. Books are one of the best ways to learn and educate yourself, and as the old saying goes, knowledge is power. Data science will continue to be a driving force for positive change in society, one analysis at a time.
Process
As a college student majoring in business, I have come to learn about the necessity and value “good” data brings over the past school year. However, I am just as passionate about writing and exploring the publishing industry, so with the help of my mentor, Amanda, I was able to speak with a data analyst to find out just that. Amanda set up career chats with other accomplished female colleagues for me to learn from and about their journeys. By supplementing what I had learned from school with the insights I gained about the industry from these conversations, I was able to get a fuller picture of how these fields intersect. In turn, I was inspired to create this piece and am excited to follow the growth of data science as a field and career opportunity grows in the publishing world.
Christine Yan
Christine Yan is a first-year student in college in New York with an avid interest in storytelling, journalism and photography. Academically, Christine aims to pursue a major in the intersection of finance and data science. She loves working on projects that connect people and business solutions. Language and writing help her express herself and her ideas, both creatively and academically. When Christine’s not writing or editing pictures, she can be found painting for fun!