Classification of Intangible Social Innovation Concepts

Research output: Contribution to conferencePaperpeer-review


In social sciences, similarly to other fields, there is exponential growth of literature and textual data that people are no more able to cope with in a systematic manner. In many areas there is a need to catalogue knowledge and phenomena in a certain area. However, social science concepts and phenomena are complex and in many cases there is a dispute in the field between conflicting definitions. In this paper we present a method that catalogues a complex and disputed concept of social innovation by applying text mining and machine learning techniques. Recognition of social innovations is performed by decomposing a definitions into several more specific criteria (social objectives, social actor interactions, outputs and innovativeness). For each of these criteria, a machine learning-based classifier is created that checks whether certain text satisfies given criteria. The criteria can be successfully classified with an F1-score of 0.83–0.86. The presented method is flexible, since it allows combining criteria in a later stage in order to build and analyse the definition of choice.
Original languageEnglish
Number of pages418
Publication statusPublished - May 2018
Event23rd International Conference on Natural Language & Information Systems - Conservatoire National des Arts et Métiers, Paris, France
Duration: 13 Jun 201815 Jun 2018
Conference number: 23


Conference23rd International Conference on Natural Language & Information Systems
Abbreviated titleNLDB2018
Internet address


  • text mining
  • social innovation
  • machine learning
  • natural language processing

Research Beacons, Institutes and Platforms

  • Manchester Institute of Innovation Research


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