Bestselling Books Project

"To read is to struggle to name, to subject the sentences of a text to a semantic transformation." — Roland Barthes

Every bookstore tells a story beyond its shelves. As one publisher noted, "Bestseller topics reflect what keeps society awake at night." This observation sparked our exploration into how we categorize and consume literature in the digital age.

We began by examining book genres and sales figures, seeking patterns in readers' interests. However, this initial approach revealed something more profound: genre itself is a social construct, as fluid and interpretative as the texts it attempts to classify.

This realization led us to explore alternative classification methods. By analyzing the top 200 book subjects from the Open Library API, we uncovered a complex network of interconnected themes and categories. Rather than imposing our own interpretation, we preserved these community-generated labels, allowing their natural relationships to emerge.

Instead of simplifying this complexity into a clean but reductive visualization, we chose to present the full tapestry of connections. While our dataset draws from open-source information and doesn't capture every bestseller ever written, this limitation aligns with our philosophy: literary classification, like any categorization system, is inherently incomplete and ever-evolving.