The Influence of Frequency, Recency and Semantic Context on the Reuse of Tags in Social Tagging Systems

TL;DR

This study investigates how frequency, recency, and semantic context affect tag reuse in social tagging systems, confirming their positive influence and highlighting the importance of folksonomy type for designing recommender algorithms.

Contribution

It applies the ACT-R cognitive model to analyze tag reuse, providing empirical evidence across six diverse social tagging datasets and emphasizing folksonomy-dependent effects.

Findings

Frequency, recency, and semantic context positively influence tag reuse.

The impact of each factor varies with folksonomy type.

Guidelines for designing tag-based recommender systems.

Abstract

In this paper, we study factors that influence tag reuse behavior in social tagging systems. Our work is guided by the activation equation of the cognitive model ACT-R, which states that the usefulness of information in human memory depends on the three factors usage frequency, recency and semantic context. It is our aim to shed light on the influence of these factors on tag reuse. In our experiments, we utilize six datasets from the social tagging systems Flickr, CiteULike, BibSonomy, Delicious, LastFM and MovieLens, covering a range of various tagging settings. Our results confirm that frequency, recency and semantic context positively influence the reuse probability of tags. However, the extent to which each factor individually influences tag reuse strongly depends on the type of folksonomy present in a social tagging system. Our work can serve as guideline for researchers and developers of tag-based recommender systems when designing algorithms for social tagging environments.