Analyzing Anime Users’ Online Forum Queries for Recommendation Using Content Analysis

Hyerim Cho, Marc L. Schmalz, Stephen A. Keating, Jin Ha Lee

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Purpose – The purpose of this paper is to improve the understanding of relevant information features for users seeking anime recommendations.

Design/methodology/approach – The study uses content analysis of 396 recommendation request threads from the online forum at Anime News Network.

Findings – In total, 19 important anime information features were identified, including Work, Theme, Genre, Audience, Mood, while Artwork/Visual Style, Audio Style, and Language were mentioned less frequently. However, when mentioned, these codes were discussed with specificity and depth.

Research limitations/implications – This study analyzed a relatively small number of 396 forum records, without demographic information. Using content analysis of online forum threads written by real users provided both informational breadth and depth. Future studies would benefit from using content analysis to investigate unfamiliar multimedia information and user groups.

Practical implications – The findings of this study can be implemented in anime-related databases and information systems to enhance organization, browsing/retrieval, and recommendation of anime, which can be further utilized for other audiovisual materials.

Originality/value – This is one of the few studies that investigate what anime users need and want. This research examines an understudied cultural medium, underserved by current research, despite an expanding community of anime users.
Original languageAmerican English
JournalJournal of Documentation
Volume74
Issue number5
DOIs
StatePublished - 3 Aug 2018
Externally publishedYes

Keywords

  • animation
  • anime
  • content analysis
  • information needs
  • multimedia
  • query analysis
  • recommendation

EGS Disciplines

  • Databases and Information Systems

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