Identification of early signals on social trends by web scraping and text analytics

In this project, we combine visual analysis with multiple data-driven approaches (such as web scraping, text mining, network analysis, spatio-temporal analysis and so on) to analyze how the concept of smart buildings is diffusing in Germany and which topics are engaging users.

• How has the smart building concept diffused spatially and over time through society?
• What are the most popular sub-topics of the smart building concept and how are these developing? Are there connections among these popular sub-topics?
• How are smart building concept technologies/products developed?
• What is the opinion online of smart buildings? What are the additional benefits of smart buildings? What are the barriers to their development?
   

• a series of available data sources (eg. Twitter, online news, council minutes) for social trend tracking
  
• a reusable scheme for collecting large amounts of unstructured text data on a specific topic from council minutes, social media and online newspapers
• a framework (tools and methods) for analyzing and visualizing social trends using massive amounts of unstructured text data