Context

The project’s main question came to mind while I was browsing through a bookstore with a friend and discussed why we are always inclined to pick up reputable New York Times bestsellers without exploring other options or conducting thorough research. This curiosity prompted me to delve deeper into the subject through the initial research.

I discovered various data points and sources that attempted to address the legitimacy of the New York Times bestseller list. Within the book industry, this list is widely regarded as the most prestigious. Attaining the status of a New York Times bestseller significantly impacts a book's sales, particularly for debut authors. However, there remains a lack of clarity regarding the methodology used to create this list, as well as the sources of the data it relies upon. In fact, there have been instances where books suspected of manipulation managed to secure the top position on the New York Times list.

Articles on NYT's allegations of manipulating the bestsellers list

Digging deeper into the topic

To gain a better understanding of the problem, I narrowed down the focus of my research. I achieved this by asking specific questions that aimed to shed light on the topic. Taking the perspective of a book reader, I delved deeper into the context and explored the curiosities of the audience. This approach allowed me to uncover valuable insights. The importance of these findings lies in their ability to inform future decisions on essay structure, data collection, and design.

Looking at the problem from different angles

Since there is no direct source of data to prove or disprove the legitimacy of the New York Times (NYT) bestsellers, I decided to approach the problem from different angles to gain a comprehensive understanding.

To determine the legitimacy of the NYT bestsellers list, I analyzed published articles discussing its accuracy, reviewed the official statement by NYT bestsellers team, compared its data with alternative sources, and considered acclaimed books not on the list.

By exploring the subject matter through these four diverse angles, it is possible to develop a more well-rounded understanding of the legitimacy of the NYT bestsellers list.

Data collection & analysis

This research employed a structured methodology to collect, process, and analyze data from two primary sources, The New York Times (NYT) and Amazon, with the goal of creating comparative charts to explore trends in bestselling books over a 12-week period from October 23rd, 2022, to January 8th, 2023. I collected data from nytimes.com and amazon.com using web scraping tools, extracted key attributes, and performed data cleaning in Google Sheets. Additionally, a meta dataset was created to encompass book metadata. I then integrated and structured the data for analysis, focusing on chronological organization by week, source, genre, and ranking. To highlight matching books between the two lists, a binary "match" column was introduced. This methodology ensured a systematic approach to dataset preparation and chart generation for insights into bestselling books across these sources during the specified timeframe.

Tools: Web Scraper (Chrome extension), Google Sheets, JavaScript, D3.js

Books bestsellers and rankings dataset

Framing the story

To authentically replicate the journalistic approach of the New York Times and ensure a comprehensive understanding of the subject matter, I decided to present this data visualization in the form of an essay. With this format, I also aim to provide the audience with the full context and guide them through my thought process as I delve into this issue. Furthermore, framing a narrative around a compelling question will further aid in keeping the audience engaged and facilitate their comprehension of the problem at hand.

Outline of the data story

Moodboard & Inspirations

An intentional color choice
Pops of color strategically accentuate data points and critical information, directing focus towards key insights within the data visualizations

In order to maintain a visual style in line with The New York Times' typical digital news presentation, I opted for a design system primarily in black and white, with a few accent colors used in the charts. This black and white palette is employed to mimic the aesthetics of print newspapers, relying on grayscale for a timeless appeal. Selective pops of color serve to draw attention to and underscore noteworthy data points.

This data visualization essay seamlessly blends vector graphics with elements of photography and videography, elevating the sophistication of the subject matter while delivering graphs that are visually accessible and straightforward for the audience to comprehend.

Mood board/ Inspirations for the visual essay

Design iterations

Design goal:
Given the intricate nature of the topic and the abundance of sources, my primary objective was to convey information in the most intuitive and comprehensible manner.

The design process underwent 3 phases of iterations and feedback. Given that both UI and data visualization graphs were developed side by side with web development and data analysis due to time constraint, substantial adjustments were made during each phase to align with insights derived from the analysis, and to address feedback received from professors and peers regarding the accessibility of the designs.

Among the visualizations, the "Evolution in appearance and ranking of NYT bestsellers" required the most design effort. The challenge lay in effectively depicting the trends within the NYT chart over the 12-week period while also incorporating the additional layer of whether these bestsellers also appeared on the Amazon Chart. In the final design, I successfully resolved this challenge by leveraging a combination of visual variables, including position, colors, and repetition, to present all these layers of data within a single graph.