Classification of Intangible Social Innovation Concepts

Research output: Contribution to conferencePaper

Abstract

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.

Bibliographical metadata

Original languageEnglish
Pages407
Number of pages418
DOIs
Publication statusPublished - May 2018
Event23rd International Conference on Natural Language & Information Systems - Conservatoire National des Arts et Métiers, Paris, France
Event duration: 13 Jun 201815 Jun 2018
Conference number: 23
http://nldb2018.cnam.fr/

Conference

Conference23rd International Conference on Natural Language & Information Systems
Abbreviated titleNLDB2018
CountryFrance
CityParis
Period13/06/1815/06/18
Internet address

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