Analysis of large amounts of political data and complex networks: mining modelling and applications in Computational Political Science

Abstract

Large volumes of unstructured political data have represented a challenge for scientific research. As a result, the development of tools aimed at extracting scientific and political information from Big Data is highly strategic. The objective of this proposal is to develop computational techniques and tools for the collection, processing and classification of political data, which provide the realization of experiments to analyze complex networks. Combining Machine Learning and Social Network Analysis, this research will develop several applications and modeling of different relations between data from Social Networking Sites, more specifically Twitter, as well as from the Open Data API of the House of Representatives. The intention is that the research generates innovation in the field of political methodology by bringing together Political Science, Computer Science and Data Science, and also contributes to to the development of Computational Political Science in Brazil. In the execution of the project, besides the open-source artifacts that will be made available to the scientific community, it is expected that a proprietary software will be produced, object of patent protection with the host institution, considering the norms and guidelines of FAPESP. (AU)