Forecasting Zombies
Analysis of AI Predictive Capacity of Genre-Specific Content Trends for Books
Bibliographic Data
| ID | 22420244 |
|---|---|
| Authors | Laetitia Cassells (0000-0002-9448-9972, University of the Witwatersrand, corresponding author), Rory Cassells |
| Year | 2026 |
| Volume | 42 |
| Issue | 3 |
| Publication date | 2026-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Publishing Research Quarterly (JOURNAL) |
| Journal identifiers | ISSN: 1053-8801 • E-ISSN: 1936-4792 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s12109-026-10070-y |
| OpenAlex | W7168134942 |
| Language | EN |
| References cited | 16 |
While there is an increasing awareness and application of artificial intelligence (AI) tools in the book publishing industry globally, it is often restricted to analysis of quantitative data and information, such as those shared by data aggregation subscription databases. This analysis is completed in a constantly evolving genre and technological tool developmental environment, where the proliferation of non-specialist tools and “scaffolded” user interactions with large language models (LLMs) are the norm. Considering the high cost of quantitative tools and the nature of machine and deep learning predictions, this paper explores the use of other AI tools for qualitative analysis, such as natural language processing and LLMs, drawing on practices reported by publishers themselves. The use of these tools to facilitate commissioning and acquisition decisions in publishing enterprises is challenged when considering the veracity and validity of these types of recommendations, as well as the lack of transparency regarding the function of these types of AI analysis tools. Using an extensive bibliography of genre-specific titles in the subject of Zombie Horror this paper presents an analysis of recommendations forecasting trends in the book market and explores the factors influencing the success of recommendations using publicly available AI tools.
Content analysis · Project commissioning · Publishing · Qualitative analysis · Authorship Attribution and Profiling · Computational and Text Analysis Methods · Digital Humanities and Scholarship
| Highly cited | No |
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