Improving Personal Tagging Consistency through Visualization of Tag Relevancy

Authors:
Qin Gao;Yusen Dai;Kai Fu
Affiliations:
Department of Industrial Engineering, Tsinghua University, Beijing, China 100084;Department of Industrial Engineering, Tsinghua University, Beijing, China 100084;Department of Industrial Engineering, Tsinghua University, Beijing, China 100084
Venue:
OCSC '09 Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009
Year:
2009

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Abstract

Tagging has emerged as a new means of organizing information, but the inconsistency in tagging behaviors of users is a major drawback which degrades both information organization and retrieval performance. The current study aims to study how the intra-personal consistency of tagging can be improved by proper tag visualization. The effects of visualization of tag frequency and visualization of the relevancy among tags on personal tagging consistency are empirically tested and compared through an experiment with 39 participants. The results show that visualization of tag relevancy improves tagging consistency significantly and reduces mental workload simultaneously; visualization of tag frequency may alleviate perceived physical demand when tag relevancy is visualized. The findings provide clear and meaningful implications for system designers.