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.

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.

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.

Future Developments

Influencer Categorization – Differentiates between traders, analysts, developers, and investors for more refined insights.

Last updated 4 months ago

Influencer Tracker

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.

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.

Future Developments

Influencer Categorization – Differentiates between traders, analysts, developers, and investors for more refined insights.

Last updated 4 months ago