Interlinkages for a megatrend on accelerating technological change and hyperconnectivity : a text mining approach

The work described in this report aims at contributing to interdisciplinarity and policy-anticipation capacity in the Joint Research Centre (JRC) of the European Commission. The authors propose, pilot and document a novel approach to explore and visualise interlinkages within (and potentially among) megatrends. Megatrends are long-term forces that are observable now and will most likely have a global impact. They can help us to identify probable and preferable futures, and to reflect on the future in a systemic way. The JRC Competence Centre on Foresight developed, curates and updates via expert workshops the Megatrends Hub, a publicly available website monitoring fourteen selected megatrends (1). In order to identify the interlinkages among the trends constituting the megatrend 'Accelerating Technological Change and Hyperconnectivity', the authors developed an approach to text-mine (2) and analyse a catalogue of 712 phenomena (3) and their descriptions from Futures Platform, a commercially available tool used to support strategic foresight (4 ). The present report describes this approach and applies it to four out of eight themes (5) identified during an expert workshop on the 'Accelerating Technological Change and Hyperconnectivity' megatrend, held in early 2021. In the context of this report, phenomena refer to all signals including emerging or weak signals but also more established trends (microand macro-trends). The authors also use the term topic when referring to a group of phenomena within a theme. The approach developed by the authors can potentially be expanded to a broader range of interlinkages (e.g. between megatrends), or targeted more in-depth at other specific themes. It is also potentially adaptable to data sources other than Futures Platform. As of writing, collaboration is on-going with the JRC Competence Centre on Text Mining and Analysis towards integrating the authors' approach with their Tools for Innovation Monitoring (TIM) for text mining and network visualisation. The focus of this report is on describing and illustrating the approach developed by the authors for detecting, describing and visualising interlinkages. This, in turn, can provide a basis for policy analysts to systematically examine, substantiate and integrate interlinkages into their analyses.