Algorithmic Gossiping: sharing and non-sharing that evolve algorithmic imaginaries to folk theories

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.

Authors

Institutions

Publication Details

Journal
Information Research an international electronic journal
Published
2025-05-19
DOI
https://doi.org/10.47989/ir30colis51922
Primary Topic
Digital Games and Media
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Algorithmic Gossiping: sharing and non-sharing that evolve algorithmic imaginaries to folk theories

Puyi Liu, Wen Zhang, Guomei Cao
Information Research an international electronic journal
Digital Games and Media
article

Algorithmic Gossiping: sharing and non-sharing that evolve algorithmic imaginaries to folk theories

Puyi Liu, Wen Zhang, Guomei Cao
article en

Abstract

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.

Information Research an international electronic journalVol. 30(CoLIS)
Central China Normal University (CN)
China Scholarship Council, Central China Normal University
Openalex Percentile: Top 86%
Digital Games and Media
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.