Trend mining with Orange – using topic modeling in futures research with the example of urban mobility

Abstract

Today, assumptions about probable future developments (at least as far as they make use of quantifiable scientific methods and are not pure speculation) are generally based on data from the past. An interesting way to analyze the future through this type of data is text mining or individual methods out of the spectrum of text mining, such as topic modeling. Topic Modeling itself is a combination of quantitative and qualitative methodology and is based on the full spectrum of social science methodology. Therefore, the method is an interesting way for futures research to analyze futures. This publication addresses the question of how a combination of different methods can contribute to trend monitoring or trend mining. For this purpose, a set of scientific publications was first generated with the help of a search query in the Web of Science (WoS), which is the basis for all evaluations and statements and topics. In essence, the method considered here should be more fully integrated into the scientific practice of futures research because it can make a valuable contribution to estimating future development based on past development.