Bibliographic record
Abstract
Purpose HotMap web search was designed to support exploratory search tasks by adding lightweight visual and interactive features to the commonly used list‐based representation of web search results. Although laboratory user studies are the most common method for empirically validating the utility of information visualization and information retrieval systems such as this, it is difficult to determine if such studies accurately reflect the tasks of real users. This paper aims to address these issues. Design/methodology/approach A longitudinal user evaluation was conducted in two phases over a ten‐week period to determine how this novel web search interface was being used and accepted in real‐world settings. Findings Although the interactive features were not used as extensively as expected, there is evidence that the participants did find them useful. Participants were able to refine their queries easily, although most did so manually. Those that used the interactive exploration features were able to effectively discover potentially relevant documents buried deep in the search results list. Subjective reactions regarding the usefulness and ease‐of‐use of the system were positive, and more than half of the participants continued to use the system even after the study ended. Originality/value As a result of conducting this longitudinal study, the author has gained a deeper understanding of how a particular visual and interactive web search interface is being used in the real world, as well as issues associated with resistance to change. These findings may provide guidance for the design, development, and study of next generation interfaces for online information retrieval.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".