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Record W2407087805 · doi:10.1145/2858036.2858537

An Evaluation of Shape Changes for Conveying Emotions

2016· article· en· W2407087805 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSet (abstract data type)Computer scienceCharacter (mathematics)Surface (topology)Cognitive psychologyPsychologyArtificial intelligenceHuman–computer interactionMathematicsGeometry

Abstract

fetched live from OpenAlex

In this paper, we explore how shape changing interfaces might be used to communicate emotions. We present two studies, one that investigates which shapes users might create with a 2D flexible surface, and one that studies the efficacy of the resulting shapes in conveying a set of basic emotions. Results suggest that shape parameters are correlated to the positive or negative character of an emotion, while parameters related to movement are correlated with arousal level. In several cases, symbolic shape expressions based on clear visual metaphors were used. Results from our second experiment suggest participants were able to recognize emotions given a shape with a good accuracy within 28% of the dimensions of the Circumplex Model. We conclude that shape and shape changes of a 2D flexible surface indeed appear able to convey emotions in a way that is worthy of future exploration.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.957

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0440.000

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 head0.278
GPT teacher head0.459
Teacher spread0.181 · 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

Quick stats

Citations49
Published2016
Admission routes2
Has abstractyes

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