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Rhythmic patterns, parameter setting and language change, phase II
Grant number: | 11/22495-6 |
Support type: | Scholarships abroad - Research Internship - Post-doctor |
Effective date (Start): | July 01, 2012 |
Effective date (End): | June 30, 2013 |
Field of knowledge: | Applied Social Sciences - Communications - Theory of Communication |
Principal Investigator: | Ciro Juvenal Rodrigues Marcondes Filho |
Grantee: | Marco Toledo de Assis Bastos |
Supervisor abroad: | Bernie Hogan |
Home Institution: | Escola de Comunicações e Artes (ECA). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
Local de pesquisa : | University of Oxford, England |
Associated to the scholarship: | 10/06243-4 - NETCLUSTERING: a theoretical model for emerging networks, BP.PD |
Abstract This research proposal is part of a larger investigation supported by FAPESP (grant number 2010/06243-4) that is developing a theoretical and analytical model for emerging networks in digital environments. In this phase of the research we are focusing on concepts and methodologies that can address the forms of a digital public opinion. In order to address that, we are using extensive statistical analysis of Twitter data. The theoretical model is based upon the description first presented to FAPESP in the original project and that consists of the clustering of users and the emergence of messages. Since the first outline of the project we have been collecting data from the public API of microblogging service Twitter, as the research methodology requires a growing volume of data and extensive computational analysis, mostly performed using R, the environment for statistical computing. During this period of the research we will evaluate concepts that underlay the theories of communication. We expect the results of this phase to describe the essentials of messages replication and to be consistent with the theoretical model we are developing. Researchers from the Department of Ecology are collaborating to this research and assisting the statistical analysis and the network visualization of Twitter data. Details of the ongoing research can be found in the research website (www.eca.usp.br/netclustering) hosted at University of São Paulo's server. (AU) | |