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

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Book cover Social Informatics (SocInfo 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8851))

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  • International Conference on Social Informatics

Abstract

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.

We would like to thank Dan Mc Farland, Dan Jurafsky, Walter W. Powell, Chris Potts, all participants of the 2014 ISS Jena conference, the 2014 KID Nice workshop, and the 2014 Summer Term Stanford Network Forum for inspiration and feedback. All opinions, and errors, remain our own.

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Author information

Authors and Affiliations

  1. Department of Business and Management, IKE, Aalborg University, Fibigerstrde 11, 9220, Aalborg, Denmark

    Roman Jurowetzki & Daniel S. Hain

Authors
  1. Roman Jurowetzki
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  2. Daniel S. Hain
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Editors and Affiliations

  1. Yahoo! Research, Barcelona, Spain

    Luca Maria Aiello

  2. Stanford Graduate School of Education, 485 Lasuen Mall, 94305-3096, Stanford, CA, USA

    Daniel McFarland

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Jurowetzki, R., Hain, D.S. (2014). Mapping the (R-)Evolution of Technological Fields – A Semantic Network Approach. In: Aiello, L.M., McFarland, D. (eds) Social Informatics. SocInfo 2014. Lecture Notes in Computer Science, vol 8851. Springer, Cham. https://doi.org/10.1007/978-3-319-13734-6_27

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  • DOI: https://doi.org/10.1007/978-3-319-13734-6_27

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13733-9

  • Online ISBN: 978-3-319-13734-6

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