SQL Queries for Automated Tweet Coding During the 2009 H1N1 Outbreak

SQL syntax for search patterns and keywords used by Infovigil for automated tweet coding and analysis during the 2009 H1N1 pandemic. The queries were authored by Chee Hong Chew of the University Health Network and are available as a 0.14 MB PDF. The dataset likely contains text-based patterns for filtering and categorizing Twitter data related to public health communication.

Use Cases

• Replicate automated tweet coding workflows based on the provided SQL search patterns.
• Analyze public sentiment and information spread on Twitter during a health crisis based on described keyword filters.
• Benchmark new social media analysis methods against established patterns from the 2009 H1N1 outbreak.
• Study the evolution of pandemic communication by applying historical query logic to contemporary data.

Strengths

• Provides specific SQL syntax from a documented public health research project.
• Authored by a researcher affiliated with the University Health Network, suggesting academic provenance.
• Focuses on a historically significant pandemic event, the 2009 H1N1 outbreak.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count and column-level documentation are absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University Health Network (author Chee Hong Chew)

Collection Method

SQL queries developed for automated tweet coding and analysis by the Infovigil system.

Time Range

2009 H1N1 outbreak period