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Behavioural Features of Various Social Groups on the Internet

2020· article· en· W3088642002 on OpenAlexvenueno aff
Galina I. Gerasimova, Nadezhda Yu. Gavrilova, П. С. Медведев

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOpinion Dynamics and Social Influence
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetInternet privacyPsychologyWorld Wide WebData scienceSociologyComputer science

Abstract

fetched live from OpenAlex

Objective: The objective of the article is to find an effective model for teaching children using modern educational technologies. Background: The relevance of the study is that the formation of communication in social networks is determined by the ability to search for strategies for social contacts. In this regard, a significant part of people uses a ready-made communicative model created on a technological basis in social networks. The issue of understanding the general structure of communication in the formation of the social structure of a person in adolescents remains debatable. Method: The article notes that the operation of social networks is governed by purely technical methods and technologies, which can be considered as prerequisites for the translation of such technologies into the space of social interactions. Results: The authors show that the possibility of a regulatory impact on adolescent behaviour fully meets the principles of organising network communities with an orientation on each person's individual characteristics. Conclusion: The use of Internet technologies allows for the growth and timely development of communication technologies for the formation of a balanced personality in a globalised world.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.456

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 head0.049
GPT teacher head0.288
Teacher spread0.239 · 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 designObservational
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
Published2020
Admission routes1
Has abstractyes

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