Opinion formation on scientific-related social subjects
In this part of the project we want to investigate how the opinion of a society evolves in which concerns scientific related subjects,by analyzing large bases of textual data. We aim at extracting patterns of relevant information, in order to construct data based models of opinion formation and evolution.
More specifically, using the NYT database, we are interested in understanding how scientific topics of high societal impact migrate from the channels restricted to scientists to the public media and how this diffusion contributes to fashion the public opinion on those particular topics. This data base is well adapted for our purpose because it runs over a very long period (roughly from1850 until now), which had seen an outstanding acceleration in scientific and technical developments that has induced significant changes in social organization.
- How can relevant information be obtained from the Big Data sources at disposal in order to build data based models of opinion dynamics? What is the role of the metadata in this endeavour?
- How can one infer the network of social contacts on the basis of these data?
- How can one capture opinion dynamics? Which are the parameters that characterize the dynamical process? How do these parameters depend on the type of media where opinion diffuses?
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