An Observatorium for Science in Society based in Social Models
Funding agencies and decision-makers seek to support research with a high social impact. To identify this research, they need tools. Traditional evaluation of research has used peer review (before publication) and bibliometric in...
Funding agencies and decision-makers seek to support research with a high social impact. To identify this research, they need tools. Traditional evaluation of research has used peer review (before publication) and bibliometric indicators (afterwards). However, these tools evaluate research in terms of the values and needs of the research community, rather than those of society. Against this background, the strategic goal of the SISOB is develop novel tools making it possible to measure and predict the social impact of research. More specifically, SISOB will develop tools to measure and predict the social appropriation of research knowledge, modelled as the product of complex interactions within and between multiple, intersecting communities of scientists, journalists, industrial, decision makers and consumers. In this setting, the project will use computer-supported Social Network Analysis (SNA) to analyze how the topology of these networks can measure and predict the social impact of research.
The specific goals of the project are thus to: (i) create a framework modelling the actors, relationships, communities and social networks involved in the social appropriation of research knowledge; (ii) design and implement tools and indicators making it possible to automatically collect, analyze and visually represent data describing these actors and their interactions; (iii) create data-driven models of specific actors, communities and networks relevant to three case studies; (iv) use the tools and indicators developed by the project to collect and analyze data relevant to the same studies; (v) use the results from these studies to validate the methods and tools developed; (vi) Implement, and release in open source, a platform for the capture and analysis of social network data relevant to measuring the social impact of research.
The case studies are: mobility of researchers, knowledge sharing and peer reviewing processes.ver más
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