MétaCan
Menu
Back to cohort
Record W2153035568 · doi:10.1109/hicss.2007.39

A System Dynamics Approach to Study Virtual Communities

2007· article· en· W2153035568 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
TopicOpen Source Software Innovations
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIncentiveComputer scienceProcess (computing)Mechanism (biology)Dynamics (music)Human–computer interactionVirtual communitySystem dynamicsWorld Wide WebArtificial intelligenceThe InternetPsychology

Abstract

fetched live from OpenAlex

In recent years, extensive studies of many interesting aspects of virtual community dynamics promoted a better understanding of this area. One of the most challenging problems facing builders of virtual communities is the design of incentive mechanisms that can ensure user participation. However, running virtual community experiments in the real world is expensive, and requires a great deal of motivation from users. In this paper we advocate a system dynamics approach to simulate the overall behaviors of participants in the communities, which can provide insights into the user motivation process, incentive mechanism evaluation and community development. A simulation model for a virtual community called Comtella is presented, and the results are very promising

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: none
Teacher disagreement score0.961
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.026
GPT teacher head0.266
Teacher spread0.240 · 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

Citations45
Published2007
Admission routes1
Has abstractyes

Explore more

Same topicOpen Source Software InnovationsFrench-language works237,207