Instagram Ad Revenue Impact of Fairness Guarantees

An empirical analysis of fairness in location-based advertising, focusing on Instagram user data. The research was conducted by Christopher Riederer at Columbia University. It examines the trade-off between fairness guarantees and advertising revenue.

Use Cases

• Analyzing the impact of fairness constraints on ad revenue based on the empirical methodology described.
• Studying inadvertent discrimination in location-based systems based on gender and race attributes mentioned.
• Evaluating the effect of different location representations on fairness outcomes as referenced in the description.

Strengths

• Analysis is based on a real-world example using Instagram data.
• The work applies fairness techniques to analyze both individual and group fairness guarantees.
• The methodology is described as applicable to more general advertising tasks beyond the specific case study.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Columbia University

Collection Method

Empirical analysis of real-world data from Instagram.