Modeling and applying an analytical process based on social web exploration to support decisions in public security
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFPE |
Texto Completo: | https://repositorio.ufpe.br/handle/123456789/53754 |
Resumo: | 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. |
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CARVALHO, Victor Diogho Heuer dehttp://lattes.cnpq.br/9961970112647545http://lattes.cnpq.br/9665695510823023COSTA, Ana Paula Cabral Seixas2023-11-27T12:03:12Z2023-11-27T12:03:12Z2023-09-14CARVALHO, Victor Diogho Heuer de. Modeling and applying an analytical process based on social web exploration to support decisions in public security. 2023. Tese (Doutorado em Engenharia de Produção) – Universidade Federal de Pernambuco, Recife, 2023.https://repositorio.ufpe.br/handle/123456789/53754Public 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.A segurança pública é um setor crítico da Administração Pública, com repercussões diretas sobre o funcionamento e o bem-estar da sociedade, além disso, é uma usuária potencial de ferramentas associadas à Ciência dos Dados e à Inteligência Artificial, para auxiliar a tomada de decisões e resolução de problemas. Suas atividades são caracterizadas por uma rede complexa de operações envolvendo ciclos de planejamento, monitoramento e execução de ações, sejam destinadas à prevenção ou à correção de problemas que podem afetar à segurança das pessoas e do patrimônio público. A web social deixa à disposição informações através de redes sociais digitais, sites pessoais, sites de notícias, blogs, e-mails, fóruns digitais, que podem ser minerados para a extração de informações. No âmbito da segurança pública, é possível realizar uma série de processos como a identificação de mensagens criminosas, a detecção de eventos ou movimentações sociais com potencial de causar danos ao patrimônio público ou às pessoas, resgate de informações para uso em processos investigativos, apoiando ações forenses ou decisões judiciais, e ainda a detecção das opiniões, sentimentos e emoções das pessoas sobre as ações executadas pelos órgãos que promovem a segurança. Esta tese tem por objetivo a proposição e aplicação de um processo analítico envolvendo fontes de dados textuais da web social para apoiar as atividades e as decisões no âmbito da gestão da segurança pública, definindo um framework para todo o processo de extração, armazenamento, tratamento, análise e visualização dos grandes volumes de informações que podem ser extraídos destas fontes. Para tanto, são empregadas diversas ferramentas, na seguinte sequencia: (i) web scraping, ou seja, a raspagem das fontes disponíveis na Internet para a obtenção de textos associados à temas de segurança pública; (ii) armazenamento dos textos em formatos específicos e em bases adequadas, criando corpora (conjuntos textuais); (iii) tratamento ou pré-processamento dos textos utilizando ferramentas de processamento de linguagem natural, para que sejam eliminados ruídos indesejados que possam prejudicar as análises; (iv) análise de dados com ferramentas de Inteligência Artificial, especificamente da Aprendizagem de Máquina e seus ramos, para detectar padrões, como no caso da análise de sentimentos ou de opiniões; (v) apresentação visual, por meio de gráficos amigáveis, possibilitando que os gestores/decisores possam ter uma compreensão adequada do fenômeno em análise. Os potenciais impactos da pesquisa, portanto, dizem respeito à geração e aplicação de instrumentos para o resgate, estruturação, e análise das informações extraídas da web social sobre temas de interesse relacionados à segurança pública. O framework analítico torna possível demonstrar, por exemplo, a evolução das postagens sobre um tema e onde elas foram geradas, auxiliando na identificação de quem os gerou e outras pessoas mencionadas, habilitando a aplicação dos resultados nas decisões estratégicas da gestão da segurança pública, resultando em ações para a melhoria dos serviços ofertados à população e no combate à desinformação que pode estar associada.engUniversidade Federal de PernambucoPrograma de Pos Graduacao em Engenharia de ProducaoUFPEBrasilAttribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/embargoedAccessEngenharia de produçãoSegurança públicaWeb socialProcesso analíticoInteligência artificialAprendizagem de máquinaMineração de textosModeling and applying an analytical process based on social web exploration to support decisions in public securityinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisdoutoradoreponame:Repositório Institucional da UFPEinstname:Universidade Federal de Pernambuco (UFPE)instacron:UFPEORIGINALTESE Victor Diogho Heuer de Carvalho.pdfTESE Victor Diogho Heuer de Carvalho.pdfapplication/pdf7856872https://repositorio.ufpe.br/bitstream/123456789/53754/1/TESE%20Victor%20Diogho%20Heuer%20de%20Carvalho.pdf31e79cbbb4b0b5efa27a121e0786dd8eMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.pt_BR.fl_str_mv |
Modeling and applying an analytical process based on social web exploration to support decisions in public security |
title |
Modeling and applying an analytical process based on social web exploration to support decisions in public security |
spellingShingle |
Modeling and applying an analytical process based on social web exploration to support decisions in public security CARVALHO, Victor Diogho Heuer de Engenharia de produção Segurança pública Web social Processo analítico Inteligência artificial Aprendizagem de máquina Mineração de textos |
title_short |
Modeling and applying an analytical process based on social web exploration to support decisions in public security |
title_full |
Modeling and applying an analytical process based on social web exploration to support decisions in public security |
title_fullStr |
Modeling and applying an analytical process based on social web exploration to support decisions in public security |
title_full_unstemmed |
Modeling and applying an analytical process based on social web exploration to support decisions in public security |
title_sort |
Modeling and applying an analytical process based on social web exploration to support decisions in public security |
author |
CARVALHO, Victor Diogho Heuer de |
author_facet |
CARVALHO, Victor Diogho Heuer de |
author_role |
author |
dc.contributor.authorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/9961970112647545 |
dc.contributor.advisorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/9665695510823023 |
dc.contributor.author.fl_str_mv |
CARVALHO, Victor Diogho Heuer de |
dc.contributor.advisor1.fl_str_mv |
COSTA, Ana Paula Cabral Seixas |
contributor_str_mv |
COSTA, Ana Paula Cabral Seixas |
dc.subject.por.fl_str_mv |
Engenharia de produção Segurança pública Web social Processo analítico Inteligência artificial Aprendizagem de máquina Mineração de textos |
topic |
Engenharia de produção Segurança pública Web social Processo analítico Inteligência artificial Aprendizagem de máquina Mineração de textos |
description |
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. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-11-27T12:03:12Z |
dc.date.available.fl_str_mv |
2023-11-27T12:03:12Z |
dc.date.issued.fl_str_mv |
2023-09-14 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
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doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
CARVALHO, Victor Diogho Heuer de. Modeling and applying an analytical process based on social web exploration to support decisions in public security. 2023. Tese (Doutorado em Engenharia de Produção) – Universidade Federal de Pernambuco, Recife, 2023. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufpe.br/handle/123456789/53754 |
identifier_str_mv |
CARVALHO, Victor Diogho Heuer de. Modeling and applying an analytical process based on social web exploration to support decisions in public security. 2023. Tese (Doutorado em Engenharia de Produção) – Universidade Federal de Pernambuco, Recife, 2023. |
url |
https://repositorio.ufpe.br/handle/123456789/53754 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ info:eu-repo/semantics/embargoedAccess |
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Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
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dc.publisher.none.fl_str_mv |
Universidade Federal de Pernambuco |
dc.publisher.program.fl_str_mv |
Programa de Pos Graduacao em Engenharia de Producao |
dc.publisher.initials.fl_str_mv |
UFPE |
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Brasil |
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Universidade Federal de Pernambuco |
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