Long Ties and Economic Prosperity in US and Mexico Zip Codes

US and Mexico data measures long ties and clustering coefficients in social networks at zip code and county levels. It is derived from reciprocal Facebook commenting activity during a 180-day snapshot period prior to November 2021. The dataset, created by Eaman Jahani, supports research on associations between network structure, disruptive life events, and economic outcomes.

Use Cases

• Analyze the association between long tie frequency and economic outcomes at the zip code level.
• Study how clustering coefficient values correlate with disruptive life events across US counties and Mexican municipalities.
• Compare network structural diversity, measured by long ties and clustering coefficient, between geographic regions in the US and Mexico.
• Investigate the relationship between long tie formation and economic opportunity access using zip code-level metrics.

Strengths

• Data provides network measures at two geographic granularities: zip codes and counties/municipalities.
• Derived from a large-scale social network (Facebook) using a defined 180-day activity snapshot.
• Explicitly designed to study associations between network structure, life events, and economic prosperity.

Limitations

• Unknown sample size and row count for the derived geographic measures.
• Network data is from a single platform (Facebook) and a specific time window, which may limit generalizability.
• Lacks direct visibility into underlying user-level data or the specific economic outcome variables used.

Provenance

Source

ICPSR Harvested Dataverse

Collection Method

Constructed from reciprocal commenting activity on the Facebook platform among users in the US and Mexico.

Time Range

180-day snapshot period prior to 2021-11-01

Freshness

Data snapshot is from 180 days prior to 2021-11-01; metadata was last updated in 2026.

Geography

United States and Mexico, aggregated to zip codes and counties/municipalities.