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Record W2133243910 · doi:10.1086/661552

The Lonely Consumer: Loner or Conformer?

2012· article· en· W2133243910 on OpenAlexaff
Jing Wang, Rui Zhu, Baba Shiv

Bibliographic record

VenueJournal of Consumer Research · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScrutinyPopularityLonelinessProduct (mathematics)FeelingPsychologySocial psychologyAdvertisingSubject (documents)MarketingBusinessPolitical science

Abstract

fetched live from OpenAlex

Despite the popularity of social networks and technologies that intend to enhance social interaction, more Americans feel lonely now than before. This research examines how loneliness affects consumers’ responses to consensus-related social cues in marketing contexts. Results from three studies show that lonely consumers prefer minority-endorsed products, whereas nonlonely consumers prefer majority-endorsed products. However, this pattern occurs only when consumers’ product preferences are kept private. When product preferences are subject to public scrutiny, lonely consumers shift their preferences to majority-endorsed products. Results also reveal the underlying mechanisms. Minority-endorsed products fit better with the feelings of loneliness, and this fit mediates the effect of loneliness and endorsement type (i.e., majority vs. minority endorsement) on product evaluations in private consumption contexts. Yet, when their preferences are subject to public scrutiny, lonely consumers are concerned about being negatively evaluated by others, and this concern causes them to conform to the majority.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.273
GPT teacher head0.536
Teacher spread0.263 · 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 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

Citations159
Published2012
Admission routes1
Has abstractyes

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