A Data-Driven Analysis of Factors Influencing Consumer Purchases of ACG Derivatives — Combining Logistic Regression and Text Mining

2025

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.1145/3766918.3766951
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

In the digital consumption era, ACG (Animation, Comic, and Game) derivative products are highly favored by Generation Z. This study investigates the influencing factors behind consumer purchases of secondary ACG derivatives. A structured questionnaire was conducted, and the data were analyzed using logistic regression to identify key predictors. To enhance analytical rigor, computing techniques such as Natural Language Processing (NLP) and K-means clustering were integrated. High-frequency keywords from online reviews were visualized via word clouds, while clustering revealed major concerns like authenticity, emotional attachment, and pricing. These computational insights supported the quantitative results, showing that emotional identity, product quality, and brand trust significantly affect consumer behavior. The study combines traditional statistical methods with intelligent computing tools, offering new perspectives for ACG marketing strategies and digital engagement.