Bacharelado em Ciência da Computação (Sede)
URI permanente desta comunidadehttps://arandu.ufrpe.br/handle/123456789/6
Siglas das Coleções:
APP - Artigo Publicado em Periódico
TAE - Trabalho Apresentado em Evento
TCC - Trabalho de Conclusão de Curso
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3 resultados
Resultados da Pesquisa
Item The digital behavior of voters in interactions with the social media posts of candidates running for elections(2022-10-06) Silva Filho, Heriberto Alexandre da; Brito, Kellyton dos Santos; http://lattes.cnpq.br/8750956715158540; http://lattes.cnpq.br/6181814500468590The extensive use of digital tools and digital marketing strategies over the last few years has become increasingly more frequent and characteristic in political campaigns Within this scenario, this study aims to investigate the use of SM in contemporary political communication, seeking to understand the features that influence the engagement of voters in posts by politicians on their social media profiles. As a case study, we have focused on the Brazilian presidential election in 2018. The investigation was based on an analysis of politicians’ posts on Instagram, Twitter, and Facebook (N = 1319) in the last two weeks before the elections, which investigated features such as functional approach, the Aristotelian rhetoric adopted, and the type of content, among others, and established relationships between these features and user engagement. This study also proposes to investigate the feasibility of using machine learning models to predict the level of engagement of the candidate's posts. Finally, another objective of this paper is to find similarities or differences between the digital campaign strategies, and their impacts on the level of engagement, of the two candidates with the best electoral results. Our main results indicate that the platform with the highest level of engagement was Instagram, together with polarized discourses that presented speeches of attack and defense or emotionally charged topics tended to engage more. Regarding the predictions, the Gradient Boosting model proved to be efficient, R² =0.77, to make the predictions. Regarding the digital campaign strategies, although the two candidates are from opposite political sides, it was possible to find more similarities, such as: functional approach, content structure, and content type, and others...than differences. However the few differences found also represent a valuable result for the understanding of the political landscape, there were divergences for example in Aristotelian rhetoric, content type, and rhetorical device. All these results helped to understand how the electorate interacts with the candidates' speeches in a new era of digital campaigning.Item Análise da acessibilidade para pessoas com deficiência visual e auditiva em redes sociais(2024-10-01) Lima, Thiago Ferreira de; Falcão, Taciana Pontual da Rocha; http://lattes.cnpq.br/5706959249737319; http://lattes.cnpq.br/5181649435278623Item Sentiment analysis of tweets related to SUS before and during COVID-19 pandemic(2021-02-19) Silva, Henrique Farias Pereira da; Andrade, Ermeson Carneiro de; Araújo, Danilo Ricardo Barbosa de; Dantas, Jamilson Ramalho; http://lattes.cnpq.br/5655706091153128; http://lattes.cnpq.br/2466077615273972; http://lattes.cnpq.br/9810796504568932The COVID-19 pandemic has affected the whole world since the beginning of 2020. In Brazil, over 70% of the population rely on the Brazil’s Unified Health System (SUS). Knowing public opinion related to SUS is very important for the improvement of services and assistance provided by such an entity. Sentiment analysis has been used in several applications including social networks and blogs to extract public opinion. Despite the fact that other papers have already worked with sentiment analysis, none of them have focused on SUS. Therefore, the goal of this paper is to analyse the sentiments shown by Brazillian Twitter users about SUS before and during COVID-19 pandemic. To reach this goal, a database of portuguese tweets regarding SUS posted between december 2019 and october 2020 was created. The tweets were pre-processed, classified and then analysed. The results show that, in most cases, users are in favor of SUS.