Visualizing Reader-Created Tags for Books on GoodReads

Oreoluwa Arowobusoye, Tina Thanh Huynh, and Anthony Tang. (2017). Visualizing Reader-Created Tags for Books on GoodReads. In Poster Proceedings of Graphics Interface 2017. Notes: 2-page abstract + poster.

Abstract

This project focuses on the question of how to design a visualization that reveals underlying relationships between books (i.e. texts) based on user-generated tags as they relate to these books. The core problem the project addresses is that main mechanisms to classify texts–either based on literary classifications or text-analytics-based classifications are either too high-level, or too low-level. Rather, a perhaps more valuable way to explore relationships between texts is to use reader-generated tags. Here, we make use of data scraped from GoodReads, a social media site where the principal artefact under discussion is a book, and accumulated book reviews. In particular, we visualize the "bookshelves" each book is classified with (these "bookshelves" are user-generated tags), and we present two sets of visualizations that allow prospective readers with the ability to compare the thematic differences between different books.

Materials

PDF File (http://hcitang.org/papers/2017-gi2017posters-visualizinggoodreads.pdf)
URL (http://hcitang.org/papers/2017-gi2017posters-visualizinggoodreads-poster.pdf)

BibTeX

@inproceedings{ore2017goodreads,
  author = {Arowobusoye, Oreoluwa and Huynh, Tina Thanh and Tang, Anthony},
  booktitle = {Poster Proceedings of Graphics Interface 2017},
  pdfurl = {http://hcitang.org/papers/2017-gi2017posters-visualizinggoodreads.pdf},
  url = {http://hcitang.org/papers/2017-gi2017posters-visualizinggoodreads-poster.pdf},
  title = {Visualizing Reader-Created Tags for Books on GoodReads},
  type = {poster},
  year = {2017},
  notes = {2-page abstract + poster}
}