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Record W4402722127 · doi:10.1145/3670947.3670975

Co-Here: an expressive videoconferencing module for implicit affective interaction

2024· article· en· W4402722127 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

VenueGraphics Interface · 2024
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceVideoconferencingHuman–computer interactionMultimedia

Abstract

fetched live from OpenAlex

Participants of one-to-many videoconferencing calls often experience a significant loss of affective feedback due to the limitations of the medium. To address this problem, we present Co-Here: a videoconferencing module that renders participant-driven animations that convey group affect without relying on categorical emotion detection or signaling. Co-Here consolidates and visualizes facial expressions and head movements of fellow videoconferencers, providing a sufficient medium for others to meaningfully construct emotional impressions. Our qualitative user study showed that the system helped users feel a sense of alignment with the emotions of others using the system. Co-Here had the most utility to presentation viewers, who reported that the system offered a low-attention alternative to gauging the sentiment of the crowd.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.709
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.064
GPT teacher head0.406
Teacher spread0.342 · 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