# What Text Design Characterizes Book Genres?

arXiv: https://arxiv.org/abs/2402.16356 · HTML: https://mlsanity.com/paper/2402.16356/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 26 references that are in the map.
- First posted on arXiv 26 Feb 2024.

## Builds on (most cited first, 13 of 13)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Quantifying Attention Flow in Transformers](https://mlsanity.com/paper/2005.00928/) (2020)
- [Character Region Awareness for Text Detection](https://mlsanity.com/paper/1904.01941/) (2019)
- [What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis](https://mlsanity.com/paper/1904.01906/) (2019)
- [SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models](https://mlsanity.com/paper/2107.09313/) (2021)
- [Aesthetic Text Logo Synthesis via Content-aware Layout Inferring](https://mlsanity.com/paper/2204.02701/) (2022)
- [Let Me Choose: From Verbal Context to Font Selection](https://mlsanity.com/paper/2005.01151/) (2020)
- [Serif or Sans: Visual Font Analytics on Book Covers and Online Advertisements](https://mlsanity.com/paper/1906.10269/) (2019)
- [Effect of Text Color on Word Embeddings](https://mlsanity.com/paper/2004.08526/) (2020)
- [Deep multi-modal networks for book genre classification based on its cover](https://mlsanity.com/paper/2011.07658/) (2020)
- [Font Style that Fits an Image -- Font Generation Based on Image Context](https://mlsanity.com/paper/2105.08879/) (2021)
- [Analyzing Font Style Usage and Contextual Factors in Real Images](https://mlsanity.com/paper/2306.12050/) (2023)

## Built on by (most cited first, 2 of 2)

- [Adaptive Data-Resilient Multi-Modal Hierarchical Multi-Label Book Genre Identification](https://mlsanity.com/paper/2505.03839/) (2025)
- [Hierarchical Book Organization for Learning-Resource Discovery using Dual-Path Graph Convolutions](https://mlsanity.com/paper/2512.21076/) (2025)

## Abstract (arXiv)

This study analyzes the relationship between non-verbal information (e.g., genres) and text design (e.g., font style, character color, etc.) through the classification of book genres using text design on book covers. Text images have both semantic information about the word itself and other information (non-semantic information or visual design), such as font style, character color, etc. When we read a word printed on some materials, we receive impressions or other information from both the word itself and the visual design. Basically, we can understand verbal information only from semantic information, i.e., the words themselves; however, we can consider that text design is helpful for understanding other additional information (i.e., non-verbal information), such as impressions, genre, etc. To investigate the effect of text design, we analyze text design using words printed on book covers and their genres in two scenarios. First, we attempted to understand the importance of visual design for determining the genre (i.e., non-verbal information) of books by analyzing the differences in the relationship between semantic information/visual design and genres. In the experiment, we found that semantic information is sufficient to determine the genre; however, text design is helpful in adding more discriminative features for book genres. Second, we investigated the effect of each text design on book genres. As a result, we found that each text design characterizes some book genres. For example, font style is useful to add more discriminative features for genres of ``Mystery, Thriller & Suspense'' and ``Christian books & Bibles.''