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Sociology of Virtual Communities and Social Software Design

2010· book-chapter· en· W2488224926 on OpenAlexaff
Daniel Memmi

Bibliographic record

VenueIGI Global eBooks · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsVirtual communitySociologySocial softwareSoftwareWorld Wide WebSocial groupSocial relationOrder (exchange)Computer scienceEpistemologyThe InternetSocial scienceBusiness

Abstract

fetched live from OpenAlex

The Web 2.0 movement is the latest development in a general trend toward computer-mediated social communication. Electronic communication techniques have thus given rise to virtual communities. The nature of this new type of social group raises many questions: are virtual communities simply ordinary social groups in electronic form, or are they fundamentally different? And what is really new about recent Web-based communities? These questions must first be addressed in order to design practical social communication software. To clarify the issue, we will resort to a classical sociological distinction between traditional communities based on personal relations and modern social groups bound by functional, more impersonal links. We will argue that virtual communities frequently present specific features and should not be assimilated with traditional communities. Virtual communities are often bound by reference to common interests or goals, rather than by strong personal relations, and this is still true with Web 2.0 communities. The impersonal and instrumental nature of virtual communities suggests practical design recommendations, both positive and negative, for networking software to answer the real needs of human users.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.018
Scholarly communication0.0060.007
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.057
GPT teacher head0.309
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2010
Admission routes1
Has abstractyes

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