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Investigating communication and social practices in real-time strategy games: are in-game tools sufficient to support the overall gaming experience?

2011· article· en· W2514890 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

VenueGraphics Interface · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceConversationRobustness (evolution)Flexibility (engineering)Human–computer interactionScreening gameNon-cooperative gameMultimediaGame theoryPsychology

Abstract

fetched live from OpenAlex

This paper discusses the social and strategic communication patterns observed during gameplay of the real-time strategy game, StarCraft II. An observational study was conducted over three weeks during which approximately 26 game matches and the social procedures by which players organized themselves and selected game options were observed. Study participants were members of a pre-existing network of friends and had adopted the Skype voice communication tool to support the game client's built-in collaboration and social networking solutions. The players were observed playing in situations of varying levels of collaboration ranging from team matches to free-for-all matches, and many forms of communication, including both strategic and social, were observed. The study findings revealed that players prefer communication tools that provide both robustness and flexibility. Preferred tools increase ease of access to other players, introduce a measure of exception handling to unify the gameplay experience, and make use of the game as a virtual watercooler---a hub which can facilitate much off-topic, yet valued, conversation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.159
GPT teacher head0.377
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