Influencer and Follower Seeding Strategies for Online Word-of-Mouth Diffusion

A dataset from the Journal of Marketing combines observational and experimental data on social media word-of-mouth. It comprises secondary data collected from X (formerly Twitter) via its API and primary data from an experiment conducted on CloudResearch. The dataset was authored by Hee Mok Park and was last updated on June 25, 2026.

Use Cases

• Compare the effectiveness of influencer versus follower seeding strategies based on the experimental design.
• Analyze the diffusion patterns of online word-of-mouth based on the social media data collected.
• Model social affirmation mechanisms based on the combined observational and experimental data.
• Validate seeding strategy hypotheses for marketing campaigns based on the described primary dataset.

Strengths

• Combines observational social media data with controlled experimental data, allowing for triangulation of findings.
• Dataset is associated with a publication in the Journal of Marketing, suggesting academic peer review.
• Last updated date is explicitly provided as 2026-06-25.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Journal of Marketing

Collection Method

Secondary data collected from X (formerly Twitter) API and primary data from a CloudResearch experiment.

Freshness

Last updated 2026-06-25 21:00:36; freshness should be verified.