social-analytics

Aggregate cross-platform social performance CSVs into benchmarks and sentiment reports.

1|Updated Mar 19, 2026

Search Tags:#analytics #benchmarking #cross-platform #social #sentiment #competitor #share-of-voice

Ready to run

npx skills add https://github.com/weisberg/agile_agentic_analytics --skill social-analytics-weisberg

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: social-analytics
Source: https://github.com/weisberg/agile_agentic_analytics/tree/main/plugins/marketing-analytics/skills/social-analytics
Command: npx skills add https://github.com/weisberg/agile_agentic_analytics --skill social-analytics-weisberg

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, scikit-learn, transformers, torch, and includes scripts (resource) components.

What problem does it solve?

Aggregates cross-platform social data to provide benchmarks, sentiment analysis, and competitive context for marketing teams.

Core Features & Use Cases

Cross-platform data aggregation from performance CSVs (social_performance_<platform>.csv)
Transformer-based sentiment analysis and crisis detection
Share of voice benchmarking and competitive benchmarking
Content performance analytics and reporting for dashboards

Quick Start

Generate a cross-platform social analytics report for the latest week.

Frequently Asked Questions about social-analytics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I aggregate cross-platform social data for competitive benchmarking?▼

You can aggregate cross-platform social data by processing performance CSVs from various platforms, which enables competitive benchmarking, share of voice calculations, and unified content performance reporting for marketing dashboards.

How does transformer-based sentiment analysis work on social media data?▼

Transformer-based sentiment analysis applies deep learning models from the transformers library to classify emotional tone in social media text, providing automated sentiment scoring and crisis detection across aggregated cross-platform data.

What is share of voice benchmarking and when do I need it for social analytics?▼

Share of voice benchmarking measures your brand's market visibility relative to competitors across social platforms. You need it when evaluating competitive context, tracking market position, or informing cross-channel marketing strategy from aggregated social performance data.

Can I use scikit-learn and pandas for social media content performance analytics?▼

Yes, this social analytics workflow leverages pandas for data manipulation and scikit-learn for model-based scoring, allowing you to process social performance CSVs and generate content performance insights for reporting dashboards.

What's the best way to calculate share of voice across multiple social platforms?▼

The best way to calculate cross-platform share of voice is to aggregate performance CSVs from all social platforms into a unified dataset, then apply deterministic scripts to benchmark your brand's visibility against competitors.

Do I need performance CSVs to run sentiment analysis and competitive benchmarking?▼

Yes, you need social performance CSVs formatted as social_performance_<platform>.csv files. These upstream data-extraction outputs serve as the required inputs for transformer-based sentiment analysis, competitive benchmarking, and share of voice calculations.