Uncovering and Modeling Emerging Technology Trends
The system not only identified topics but also placed them on a spectrum to show how close they were to each other. This allowed us to identify potential areas of overlap and combination between emerging technologies, providing valuable insights for businesses and researchers alike.
Uncovering Emerging Technology Trends through Clustering of News Data
This project aimed to gain insights into the development of emerging technologies and their interrelatedness. In collaboration with Dow Jones, we received a data export of 959,318 news articles with keywords such as "Artificial Intelligence", "Autonomous Systems", "Biotechnology", "Circular Economy", "Cybersecurity", "Energy Supply", "Future Materials", and "Quantum Technologies". By using an unsupervised clustering approach, we were able to identify relevant clusters and their interrelationships. The system not only identified topics but also placed them on a spectrum to show how close they were to each other. This allowed us to identify potential areas of overlap and combination between emerging technologies, providing valuable insights for businesses and researchers alike.
What data we used
— 959,318 news articles with keywords, such as "Artificial intelligence", "Autonomous systems", "Biotechnology", "Circular economy", "Cybersecurity", "Energy supply", "Future materials" or "Quantum technologies"
— Dow Jones API Factiva
Objectives
— Identify relevant clusters and interrelationships between emerging technologies.
— Determine potential areas of overlap and combination between emerging technologies.
— Provide valuable insights for businesses and researchers into emerging technology development.
Deliverables
— Cluster report on emerging technologies and interrelationships
— Visual representation of clusters and placement on spectrum
— Recommendations for potential technology overlap and combination
