Votre recherche
Résultats 3 ressources
-
Social innovation (SI) is a promising concept that has been developed and mobilized in academia, government policies, philanthropic programs, entrepreneurial projects. Scholars propose multiple conceptions and categorization of what is SI (trajectories, approaches, theoretical strands, paradigms, streams). Some recent work has also addressed the question of who is doing SI. In both cases, the what and the who remain the key characteristic of SI. Two approaches are confronted: one where SI is more presented as a concept that reproduces the neoliberal–capitalist societies; a second that conceives SI as a transformative and emancipatory pathway. With this article, I contribute to the possibilities to conceive SI as performative concept. My proposition is to analyze SI as a discourse with precise performative practices and apparatus. By doing so, it allows scholars and practitioners to better reflect and identify the effects, tensions and ambivalence and possibilities of SI. Moreover, it gives us few key aspects of what might constitute an emancipatory social innovation.
-
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.
-
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.
Explorer
Sujet
- Concepts
- Innovation sociale (3)
- Libre accès (2)
- litterature (2)
- Sciences sociales (2)
- Théorie (1)
- Université (1)
Type de ressource
- Article de colloque (2)
- Article de revue (1)
Définitions
- Termes liés (1)
- Théories (1)