Year: 2025
Type: article
Abstract: This project presents an Advanced Twitter Analytics and User Behavior Prediction System that leverages machine learning and natural language processing to enhance platform security, user engagement, and data-driven decision-making. It features bot detection, advanced sentiment analysis (detecting emotions like joy, anger, and sarcasm), abusive content identification, real-time trend analysis, and influencer impact assessment. These capabilities help curb misinformation, ensure user safety, prevent trend manipulation, and identify credible influencers. Overall, the system promotes a safer, more transparent, and intelligent Twitter experience for users, businesses, and policymakers.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409802337