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Record W2201947321 · doi:10.5072/zenodo.309714

Privacy aspects of health related information sharing in online social networks

2013· article· en· W2201947321 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
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInternet privacyAffect (linguistics)Risk perceptionPerceptionInformation sharingPersonally identifiable informationSocial network (sociolinguistics)Information privacyComputer scienceBusinessPsychologyComputer securitySocial mediaWorld Wide Web

Abstract

fetched live from OpenAlex

Online social networks (OSNs) have formed virtual social networks where people meet and share information. Among all shared information, health related information (HRI) has received considerable attention from researchers and individual users. While considered beneficial, sharing HRI, which is personal in nature, comes with its privacy drawback. Privacy is a process of boundary regulation that is related to the individual and her perception of the surrounding environment. As a result, the subjective privacy risk perceptions associated with sharing HRI in OSN have driven people to adopt different types of behaviour, both in terms of HRI sharing and privacy risk mitigation. Through an online survey, we examined factors that affect users' perceived privacy risks along with their risk-mitigating behaviour, when it comes to sharing HRI in OSNs. The results suggest that the majority (over 95%) of participants share some HRI, with the type and the recipient of the shared HRI being the key factors that affect the perceived privacy risk and the risk-mitigating behavioural responses.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.954

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 head0.034
GPT teacher head0.312
Teacher spread0.278 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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