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1 TAO - Machine Learning and Optimisation LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623 2 LRI - Laboratoire de Recherche en Informatique 3 CNRS - Centre National de la Recherche Scientifique 4 University of Greenwich 5 Middlesex University London

Abstract : The paper investigates the place of visual tools in mixed-methods research on social networks, arguing that they can not only improve the communicability of results, but also support research at the data gathering and analysis stages. Three examples from the authors- own research experience illustrate how sociograms can be integrated in multiple ways with other analytical tools, both quantitative and qualitative, positioning visualization at the intersection of varied methods and channelling substantive ideas as well as network insight in a coherent way. Visualization also facilitates the participation of a broad range of stakeholders, including among others, study participants and non-specialist researchers. It can support the capacity of qualitative and mixed-methods research to reach out to areas of the social that are difficult to circumscribe, such as hidden populations and informal organisations. On this basis, visualization appears as a unique opportunity for mixing methods in the study of social networks, emphasizing both structure and process at the same time.

Keywords : Data Visualization Relational Data Social Networks Sociograms Mixed Methods Qualitative Research





Autor: Paola Tubaro - Louise Ryan - Alessio D-Angelo -

Fuente: https://hal.archives-ouvertes.fr/



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