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Record W2017171200 · doi:10.1145/1878151.1878167

Online social networks for personal informatics to promote positive health behavior

2010· article· en· W2017171200 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocial mediaHealth informaticsSocial network (sociolinguistics)Computer sciencePersonal networkInformaticsPersonal information managementInternet privacyKnowledge managementData scienceWorld Wide WebInformation systemPublic healthManagement information systemsMedicineEngineering

Abstract

fetched live from OpenAlex

Social network services are becoming increasingly popular, and people are using these networks to obtain and share information. The application of social network and social media to the collection, storage and review of personal information presents opportunities for improved personal health management. This paper presents a survey of the literature on the models for the use of online social networks and models for health behavior change. These are then combined to present a framework for health behavior change through social media. This framework is then used to develop a prototype for the system design. Categories and Subject Descriptors H.5.2 [Information Interfaces and Presentation]: User Interfaces – prototyping, theory and methods, user-centered

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score0.409

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)0.0000.000

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 head0.023
GPT teacher head0.338
Teacher spread0.315 · 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

Citations52
Published2010
Admission routes1
Has abstractyes

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