International Conference on Social Informatics

SocInfo 2014: Social Informatics pp 359-383 | Cite as

Mapping the (R-)Evolution of Technological Fields – A Semantic Network Approach

  • Roman Jurowetzki
  • Daniel S. Hain
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8851)


The aim of this paper is to provide a framework and novel methodology geared towards mapping technological change in complex interdependent systems by using large amounts of unstructured data from various recent on- and offline sources. Combining techniques from the fields of natural language processing and network analysis, we are able to identify technological fields as overlapping communities of knowledge fragments. Over time persistence of these fragments allows to observe how these fields evolve into trajectories, which may change, split, merge and finally disappear. As empirical example we use the broad area of Technological Singularity, an umbrella term for different technologies ranging from neuroscience to machine learning and bioengineering, which are seen as main contributors to the development of artificial intelligence and human enhancement technologies. Using a socially enhanced search routine, we extract 1,398 documents for the years 2011-2013. Our analysis highlights the importance of generic interface that ease the recombination of technology to increase the pace of technological progress. While we can identify consistent technology fields in static document collections, more advanced ontology reconciliation is needed to be able to track a larger number of communities over time.


Technological change transition technology forecasting natural language processing network analysis overlapping community detection dynamic community detection 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Roman Jurowetzki
    • 1
  • Daniel S. Hain
    • 1
  1. 1.Department of Business and Management, IKEAalborg UniversityAalborgDenmark

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