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Record W2787103580 · doi:10.22215/etd/2014-10508

"r u mad @ me?": Social anxiety and interpretation bias in computer-mediated contexts

2014· dissertation· en· W2787103580 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
Typedissertation
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsCarleton University
Fundersnot available
KeywordsSocial anxietyPsychologyInterpretation (philosophy)Communication sourceContext (archaeology)AnxietyVignetteCognitive biasSocial psychologyDevelopmental psychologyCognitive psychologyCognition

Abstract

fetched live from OpenAlex

Symptoms of social anxiety are common, and can cause significant impairments to social and occupational functioning. Social anxiety may present unique challenges in the period of emerging adulthood, as peer interactions become increasingly important. Interpretation bias, the tendency to ascribe threatening interpretations to ambiguous social situations, is one of the cognitive distortions commonly associated with the development and maintenance of social anxiety. The goal of this dissertation was to examine the phenomenon of interpretation bias among emerging adults in response to text messages, a previously under-studied context of computer-mediated communication (CMC). In Study 1, a new vignette measure of interpretation bias in the context of text messaging (IB-CMC) was developed and piloted with a sample of N = 215 undergraduates aged 18-25 years. This new measure displayed good psychometric properties and evidence of construct validity. For example, negative interpretation bias in CMC was found to be associated with two previously established measures of interpretation bias in face-to-face situations, as well as with symptoms of social anxiety. The goal of Study 2 was to examine the effects of text-based nonverbal cues to emotion (emoticons) on interpretation bias in text messaging. For this study, vignettes were modified to include positive emoticons (‘:)’). In a sample of N = 219 undergraduates, the presence of positive emoticons was found to both reduce negative interpretations and increase benign interpretations for all users, independent of levels of social anxiety. In Study 3, the effect of sender characteristics (specifically, gender of sender) was examined in a sample of N = 353 undergraduates (159 male, 194 female). Overall, participants interpreted ambiguous text messages from female senders as more negative and less benign than messages from male senders, and this effect was particularly pronounced among male participants. Results are discussed in terms of implications for the understanding of the cognitive processes underlying social anxiety and theories of computer-mediated communication.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.784

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 science0.0010.000
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 head0.015
GPT teacher head0.275
Teacher spread0.260 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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Same topicDigital Communication and LanguageFrench-language works237,207