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30 -March -2017
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The strategic goal of SISOB is to develop novel tools making it possible to measure and predict the social impact of research. More specifically, SISOB will measure and predict one specific aspect of this impact - namely the social appropriation of scientific knowledge, generated by research - the way economic and social actors take research results and use them to produce new products, new services and new ideas. As we will see, this process depends essentially, on interactions between different actors in the process, and on the channels of social communication on which these interactions depend.


Dynamics of knowledge


Current evaluations of the quality of scientific research are conducted on (at least) two different levels. On the lower level evaluation focuses on individual "items" of research incorporated in scientific papers, conference presentations and patents. At a higher level, evaluators consider the aggregate output of researchers, research groups, institutions and communities. In both cases, the main tool used in assessment is the evaluation of individual outputs - either via peer-review or by bibliometrics measures such as citation indices. The main difference between evaluation at lower and higher levels of aggregation is that while in the former case outputs are reviewed individually, in the latter they are aggregated to generate a "score" or a "ranking".

Both classes of measurements have been the subject of much criticism about their in-built conservatism and bias, and their potential for manipulation. The most radical criticism is that while current methods are relatively good at identifying the scientific quality of individual research outputs, they are extremely poor at identifying research likely to have a strong positive impact on society. The authors of this proposal would argue that the reason for this failure is undue emphasis on individual research outputs, and a lack of attention to the networks of people, institutions and communities that produce these outputs.

SISOB's basic assumption is that the social appropriation of the knowledge generated by researchers is the product of complex interactions within and between complex communities and networks of scientists, journalists industrial and political decision makers and consumers. These communities are organized into multiple, intersecting "social networks", each with their own specific topologies. In this setting, SISOB's research strategy depends on computer-supported Social Network Analysis (SNA) - the use of electronic data to analyze specific networks and the way information flows through the network.

Specific objectives:

To achieve the goals just described, SISOB will pursue a number of Specific Objectives:

SO1: Create a general framework modelling the actors, relationships, communities and emergent research social networks involved in the production of scientific research, in the dissemination of research results and in the translation of these results into products, services and socially important ideas.

SO2: Design and implement tools and indicators which make it possible to automatically collect, analyze and visually represent data describing the actors and their interactions.

SO3: Create data-driven models of specific actors, communities and networks relevant to the three case studies mentioned above.

SO4: Use the tools and indicators developed by the project to collect and analyze data relevant to the three case studies.

SO5: Use the results from these studies to validate the methods and tools developed by the project.

SO6: Implement, and release in open source, a platform for the capture and analysis of social network data relevant to measuring the social impact of science, including data from communities and networks not included in the SISOB case studies.