Social & Health Monitoring - Sentiment Analysis & Weak Signal Detection

SeafaringIT

StageSur site4 à 6 moisDate limite : 23 févr. 2026
NLP/LLMsSocial Listeningsentiment analysisTopic ModelingData Analytics / Data EngineeringAnalyse de données / Business IntelligenceEthics

Postuler

Description

  • Goals:
  • Build an automated social listening system for health and social sector conversations
  • Detect sentiment trends, emerging issues, and weak signals
  • Provide actionable insights for proactive decisions
  • Student roles: Data engineers, NLP specialists, data scientists, BI developers, ethics specialists
  • Expected outcomes: Social monitoring platform with data collection, sentiment analysis, trend detection, dashboards, and ethical evaluation
  • Key features:
  • Data collection from public APIs/sources with normalization
  • Data anonymization and privacy protection
  • Sentiment analysis and topic modeling
  • Peak detection and weak-signal identification
  • Real-time dashboards with alerts
  • Trend analysis and reporting
  • Data quality evaluation and bias assessment
  • Improvement roadmap, ethical guidelines, limitations
  • Technologies: Python, NLP libraries (NLTK, spaCy, transformers), sentiment models, topic modeling (LDA, BERTopic), data collection APIs, anonymization tools, BI tools (Tableau, Power BI), visualization libs