Banca de DEFESA: VICTOR DIOGHO HEUER DE CARVALHO

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : VICTOR DIOGHO HEUER DE CARVALHO
DATE: 14/09/2023
TIME: 09:00
LOCAL: Online
TITLE:
KEY WORDS:

Public Security. Social Web. Analytical Process. Artificial intelligence.
Machine Learning. Text mining.

PAGES: 261
BIG AREA: Engenharias
AREA: Engenharia de Produção
SUMMARY:

Public security is a critical sector of Public Administration, with direct repercussions on
the functioning and well-being of society; it is a potential user of tools associated with Data
Science and Artificial Intelligence to assist decision-making and problem-solving. Its activities
are characterized by a complex network of operations involving cycles of planning, monitoring,
and carrying out actions aimed at preventing or correcting problems that may affect the security
of people and public property. The social web makes information available through digital social
networks, personal sites, news sites, blogs, emails, and digital forums, which can be mined for
information extraction. In the context of public security, it is possible to carry out a series of
processes such as the identification of criminal messages, the detection of events or social
movements with the potential to cause damage to public property or people, retrieval of
information for use in investigative processes, supporting forensic actions or judicial decisions,
and the detection of people's opinions, feelings, and emotions about the actions taken by the
agencies that promote security. This thesis aims to propose and apply an analytical process
involving textual data sources from the social web to support activities and decisions within the
scope of public security management, defining a framework for the entire process of extraction,
storage, treatment, analysis, and visualization of the large volumes of information that can be
extracted from these sources. To this end, several tools are used in the following sequence: (i)
web scraping to obtain texts associated with public security issues; (ii) storage of texts in specific
formats and appropriate bases, creating corpora (text sets); (iii) treatment or pre-processing of
texts using natural language processing, to eliminate unwanted noise that could impair analysis;
(iv) data analysis with Artificial Intelligence tools, specifically Machine Learning and its
branches, to detect patterns, as in the case of the analysis of feelings or opinions; (v) visual
presentation, through friendly graphics, enabling managers/decision makers to have an adequate
understanding of the phenomenon under analysis. Therefore, the potential impacts of the research
concern the generation and application of instruments for the rescue, structuring, and analysis of
information extracted from the social web on topics of interest related to public security. With the
analytical framework, it becomes possible to demonstrate, for example, the evolution of posts on
a topic and where they were generated, helping to identify who generated them and other people
mentioned, enabling the application of the results in the strategic decisions of the public security
management, resulting in actions to improve the services offered to the population and in the
fight against disinformation that may be associated.

COMMITTEE MEMBERS:
Externo à Instituição - ROBSON DE OLIVEIRA ALBUQUERQUE
Externo à Instituição - JOSÉ MARIA MORENO-JIMÉNEZ
Presidente - 1385501 - ANA PAULA CABRAL SEIXAS COSTA
Interna - 2292895 - DENISE DUMKE DE MEDEIROS
Interna - 2732514 - ISIS DIDIER LINS