Conceptualising perceived AI content appeal through bibliometric mapping of digital content research

This deposit contains the bibliographic dataset in CSV format and the documented search query supporting the study “Conceptualising perceived AI content appeal through bibliometric mapping of digital content research.” The dataset represents a corpus of 184 English-language journal articles retrieved from Scopus on 7 October 2026. The documented retrieval process initially identified 330 records. Restriction to the Business, Management and Accounting subject area reduced the results to 214 records. Further restrictions to article document type and English language produced the final corpus of 184 records. The search strategy combines three groups of terms: content and advertising appeal; behavioural intentions, including purchase, engagement and sharing intentions; and digital marketing and related communication channels. The accompanying query document records the Boolean search terms and database filters. The CSV dataset supports bibliometric mapping using Biblioshiny, the interface to the bibliometrix package in R. The research examines the literature informing the conceptual development of perceived AI content appeal (PACA), with AI-generated time-travel content as its focal application. This deposit documents the bibliographic corpus and retrieval strategy underlying the study.