Algorithmic Gossiping: sharing and non-sharing that evolve algorithmic imaginaries to folk theories - Cao, Gaohui; Wen, Zhang; Liu, Puyi (Information research, 2025)
Introduction. This paper presents a work-in-progress diary study exploring how algorithmic gossiping contributes to the transformation of individual, momentary algorithmic imaginaries into shared and consolidated folk theories. Method. This study utilises Douyin as the research site, employing an integrated approach that combines the critical incident technique with diary methods to capture significant moments, encompassing the formation, sharing and reception of participants’ algorithmic imaginaries. Analysis. A conventional content analysis method was utilised to analyse the 82 diary entries. Results. Our preliminary findings suggest that algorithmic gossiping plays a pivotal role in the construction of users’ algorithmic knowledge as it confirms and articulates their algorithmic imaginaries while breaking existing bias. Conclusion. The initial findings on algorithmic gossiping highlight its role in transforming algorithmic imaginaries into folk theories and its potential to unify the current array of concepts in the field of algorithmic-related information behaviour at individual and meso levels.