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Record W1577738302 · doi:10.1108/14684520911001909

An examination of social tagging interface features and functionalities

2009· article· en· W1577738302 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOnline Information Review · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBookmarkingComputer scienceInterface (matter)World Wide WebFocus (optics)PopularityExploratory searchSocial mediaUser interfaceVariety (cybernetics)Key (lock)Information retrievalHuman–computer interactionTag systemTag cloudArtificial intelligence

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to report on a comparative and analytical examination of ten social tagging systems' interfaces and their features and functionalities. The specific objective of the study was to examine the ways in which the user interfaces of social tagging systems encourage and provide users with features to assign, explore, browse and make use of tags during their interaction with social tagging sites. Design/methodology/approach The user interface features and functionalities of ten social tagging sites (six social bookmarking and four social media sharing sites) are examined. A categorisation of tag‐related features is developed for analysis. The sites are selected based on such criteria as popularity, variety of site type, and inclusion of tagging features and content type. Findings The findings of this study show that there is an emerging interface design paradigm with respect to social tagging sites that reflects a particular focus on exploratory search and browsing features and services. Some of the key areas discussed are: user tagging features; exploratory and tag browsing features; and interface layout. Practical implications The findings of this study of the user interface features of social tagging sites provide a comprehensive picture of the possible and potential features that can be incorporated into new social tagging systems. Based on the evidence found in the examined social tagging interfaces, recommendations are made on the design of tag posting, tag use, tag browsing, tag lists and tag clouds. The design recommendations offer ideas for the development of more sophisticated exploratory and interactive user interfaces for social tagging systems. Originality/value This is the first paper that reports on a comparative and exploratory examination of social tagging user interface features and functionalities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.346
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it