> For the complete documentation index, see [llms.txt](https://asknoel.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://asknoel.gitbook.io/docs/asknoels-tech/noels-intelligence/influencer-tracker.md).
# Influencer Tracker
Influencer Tracker enables **ASKNOEL** to track and analyze discussions from **key opinion leaders (KOLs)** across social platforms like **X (Twitter)** and **Telegram**. By monitoring **sentiment, engagement, and trending topics**, this tool provides actionable insights into **emerging narratives** and their potential impact on the market.
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#### **Key Features**
* **Influencer Activity Tracking** – Monitors tweets, discussions, and group messages from analysts, investors, and project leaders.
* **Sentiment Analysis** – Utilizes **NLP models** to classify market sentiment as **positive, negative, or neutral**.
* **Trend Identification** – Detects frequently mentioned assets, themes, and emerging narratives shaping market trends.
* **Engagement Metrics** – Analyzes responses, interactions, and virality to gauge the level of influence.
* **Historical Data Retention** – Archives KOL discussions for in-depth trend analysis and pattern recognition.
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#### **Technical Implementation**
* **API & Web Scraping** – Extracts structured data from social media and community platforms for real-time tracking.
* **Natural Language Processing (NLP)** – Evaluates sentiment, context, and relevance of discussions to determine market influence.
* **Real-Time Monitoring & Alerts** – Notifies users of **significant shifts** in key conversations or emerging trends.
* **Data Aggregation & Visualization** – Organizes insights into structured, actionable reports for strategic decision-making.
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#### **Future Developments**
* **Influencer Categorization** – Differentiates between **traders, analysts, developers,** and **investors** for more refined insights.