MétaCan
Menu
Back to cohort
Record W115553465

For a Fee: The Impact of Information Pricing Strategy on the Pattern and Effectiveness of Word-of-Mouth via Social Media

2013· article· en· W115553465 on OpenAlexaff
Hyelim Oh, Animesh Animesh, Alain Pinsonneault

Bibliographic record

VenueInternational Conference on Information Systems · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsMcGill University
Fundersnot available
KeywordsWord of mouthNewspaperSocial mediaPromotion (chess)AdvertisingProduct (mathematics)BusinessMarketingPricing strategiesComputer scienceWorld Wide WebPolitical sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

With the new realities of the digital age, print newspapers are experimenting with different pricing models for their online content. Using NYT’s paywall rollout as a natural experiment, our study finds that a firm’s information pricing policy influences the pattern and effectiveness of online word of mouth (WOM) in social media. Using difference-in-difference-indifferences analysis, we find that implementing a paywall (i.e., charging for the content which was earlier available for free) has a disproportionate impact on WOM for popular and niche articles, creating a longer tail in the content sharing distribution. Further, we find that the impact of WOM on NYT’s website traffic weakens significantly after the introduction of NYT’s paywall. These results show that information pricing strategy has implications for product and promotion strategies. The study offers novel and important implications for the theory and practice of strategic use of social media and information pricing strategy.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.402

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 studies0.0000.000
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 head0.041
GPT teacher head0.324
Teacher spread0.283 · 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 teacher head, 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

Citations2
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueInternational Conference on Information SystemsSame topicDigital Marketing and Social MediaFrench-language works237,207