MétaCan
Menu
Back to cohort
Record W2558413523

The Influence of Culture on the Expression of Emotions in Online Social Networks

2016· article· en· W2558413523 on OpenAlexaffabout
Cathia Papı

Bibliographic record

VenueESSACHESS/Essachess · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsUniversité TÉLUQ
Fundersnot available
KeywordsExpression (computer science)SociologyPsychologySocial psychologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Seeking to understand the influence of culture on the expression of emotions in online social networks, we analyzed four Facebook groups -two from Quebec, Canada and two from Colombia -created following unexpected deaths.Comparison of the messages posted in these groups reveals a stronger tendency to maintain a virtual relationship with the deceased by Canadians than by Colombians.Among the former, the deceased is more often asked to and thanked for watching over the living, and testimonies of love addressed to the deceased are more numerous than among the latter.Among the latter, the strength of the links maintained with the deceased justifying the present pain and evocation of the mourners' Catholic beliefs are relatively more frequent.Finally, while the Canadian Quebecers' messages would presumably be written in French and those of Colombians in Spanish, it is interesting to observe a certain presence of English to express feelings of loss and love in the four groups, as well as a certain affinity between North American virtual bereavement practices and those seemingly more characteristic of women, the main contributors in all four groups.

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.

How this classification was reachedexpand

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.443

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.260
Teacher spread0.218 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueESSACHESS/EssachessSame topicMedia, Religion, Digital CommunicationFrench-language works237,207