Conventional methods like surveys struggle to capture elite networks in conflict-ridden states such as Nigeria.

Method Innovation

This paper introduces scraping algorithms—leveraging co-occurrences at public events—to reconstruct political and social interaction networks.

Validity tests against existing datasets show the technique effectively recreates interaction-based ties but falls short for capturing behavioral similarities. Measurement error remains a challenge regardless of method.

Nigeria Case Study

Applying this scraping approach to Nigeria reveals that patronage—defined by public connectivity patterns—is not a primary factor in national oil company appointments.

This finding underscores the limitations of relying solely on observable co-occurrences when analyzing elite behavior.

Implications for Network Analysis

The study demonstrates how scraping algorithms offer feasible alternatives where intrusive data collection is impractical.

It highlights that political science theories focusing on individual interactions must account for potential measurement gaps.