Embracing emojis: prototyping mood enhanced information systems for fiction readersWan-Chen Lee, Li-Min Cassandra Huang, Juliana HirtJournal of Documentation, Vol. ahead-of-print, No. ahead-of-print, pp.-
This study aims to understand fiction readers’ perspectives on the strengths and concerns of incorporating emojis into information systems for fiction. To solicit readers’ feedback, the authors adopted Cho et al.’s (2023) model of three families of fiction mood categories as the theoretical framework. Based on this framework, prototypes of interface designs that implemented textual mood descriptors and/or emojis were developed.
Eighteen adult fiction readers at a US public university were recruited for online interviews. The participants shared their insights into the prototypes and their fiction search and review experiences.
Most participants preferred designs that support both mood terms and emojis. The findings highlighted the potential of emojis to improve metadata inclusivity and serve diverse users’ needs. Technical challenges and accessibility issues for blind or visually impaired users were noted as limitations of emoji implementation.
Based on established theoretical frameworks and emoji mappings for mood categories, this study advances the progress of implementing emojis into information systems for fiction. The findings will inform user-centered interface designs that support the description, search and review of fiction.
