The Influence of Frequency, Recency and Semantic Context on the Reuse of Tags in Social Tagging Systems
This work provides guidelines for researchers and developers designing tag-based recommender systems, though it is incremental as it applies an existing cognitive model to new data.
The study investigated how frequency, recency, and semantic context affect tag reuse in social tagging systems, confirming that all three factors positively influence reuse probability, with the extent varying by folksonomy type across six datasets.
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.