Influence Classification

This is a text and numeric-based statistical model to analyze English language media posts model . It analyzes text, time features, profile features and extracted data to provide estimates for future reach, impressions and engagement rate.

Statistics

Example Use Cases

The Influence Classifier is designed to evaluate and predict the potential reach and engagement of social media posts. By analyzing both the text and metadata, it estimates how influential a piece of content or account may be. Use the Influence Classifier to identify which posts, creators, or campaigns are likely to generate the most impressions or audience interaction. When combined with topic classifiers, it can help track which types of content gain the most traction within specific themes, and or discover which creators are driving the most engagement.

Output

The Influence classifier provides 3 numeric value labels. The label value is one of ‘environmental’, ‘social’, ‘governance’ depending on the ESG topic; or ‘none’ if no ESG topic is detected in the post.

"enrichment": { 
    "influence": {
      "reach": 8400,
      "impressions": 12000,
		  "engagement": 0.0234
      }
}

This tells you it will reach about 8,400 unique accounts, and be viewed approximately 12,000 times total that, and that roughly 2.34% of people who see the post will engage with it,.