6. Botswana Relational Report: Online Content Volume – to – Online Sentiment

This report uses a complex series of algorithms to identify and quantify connections/relationships between the online volume and sentiment content postings for Key Indicators (SIGINT Category). The resulting data is graphed to provide visualizations of potential correlation and causality relationships.

This report includes:

1. Society Related Content Volume/Sentiment Analysis
2. Political Related Content Volume/Sentiment Analysis
3. General IntelligenceRelated Content Volume/Sentiment Analysis
4. International Relations Related Content Volume/Sentiment Analysis
5. Health Related Content Volume/Sentiment Analysis
6. Environment Related Content Volume/Sentiment Analysis
7. Economic Related Content Volume/Sentiment Analysis
8. Military Related Content Volume/Sentiment Analysis

Cross-examination of Volume and sentiment is an increasingly popular area of research that can unveil hidden predictive information as well as demonstrate how this data can be utilized for monitoring and decision making. Understanding the relationship between the volume and tone of each SIGINT Category can represent both opportunities and potential threats for the country’s prosperity and national security.

This report aims to identify and quantify links between the weekly compiled sentiment levels of the source datasets and the volume movements of those same datasets. These statistical correlations can be useful information for determining and understanding if, and to what extent, increases or decreases in the content volume can be a predictor of sentiment changes. In many cases the relationship will be inverse.

For instance, when political volume increases you may see a decrease in the sentiment. The comparative analyses are processed through the Talos AI algorithm to provide a percentage Correlation/Causality score of an SIGINT Category’s Volume and sentiment. These scores can be compared to better understand and predict causation