Replication Data for COVID-19 Conspiracy Theory Spread on Social Media

Replication data and code accompany a study on the spread of COVID-19 conspiracy theories and content moderation effects. The dataset provides anonymized social media data in compliance with EU GDPR and the Technical University of Munich's privacy policy. Orestis Papakyriakopoulos and colleagues authored the original research paper.

Use Cases

• Analyze the spread patterns of COVID-19 conspiracy theories based on anonymized social media data mentioned in the description
• Evaluate the effects of content moderation interventions based on the study's replication framework
• Replicate computational social science findings on misinformation using the provided Python code
• Study the relationship between platform policy and conspiracy theory discourse based on the dataset's context

Strengths

• Data is anonymized according to EU General Data Protection Regulation standards
• Includes Python code to replicate the findings of the associated academic study
• Originates from a research project at the Technical University of Munich

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• The description notes some figures and coding labels deviate from the final paper version

Provenance

Source

Technical University of Munich

Collection Method

Likely collected from social media platforms, anonymized for research.