Twitter Sentiment Geographical Index: Global Well-Being Metrics from 2012 to Present

Monthly sentiment index data from 2012 to the present, derived from Twitter posts to monitor subjective well-being. The dataset provides scores at four geographical levels: globe, country, state/province, and county/city. It is a joint effort of the Sustainable Urbanization Lab at MIT and the Center for Geographic Analysis at Harvard.

Use Cases

• Tracking regional sentiment trends over time based on the monthly temporal granularity.
• Correlating subjective well-being with economic or social indicators using the geographical sentiment scores.
• Monitoring public mood at high spatial resolution based on the county/city level data.
• Analyzing sentiment volatility or recovery patterns after major events using the time-series index.

Strengths

• Covers a time range from 2012 to the present, providing longitudinal data.
• Offers four levels of geographical granularity: globe, country, state/province, and county/city.
• Updated on a monthly basis, suggesting regular maintenance.
• Includes a count (N) of posts generated for each data point, providing context for the sentiment score.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect geographic and linguistic bias inherent to Twitter's user base.

Provenance

Source

Sustainable Urbanization Lab at MIT and Center for Geographic Analysis at Harvard.

Collection Method

Likely derived from sentiment analysis of Twitter posts.

Time Range

2012 to present

Freshness

Updated monthly.

Geography

Global, with breakdowns by country, state/province, and county/city.