03.1 - Graduação (UAST)
URI permanente desta comunidadehttps://arandu.ufrpe.br/handle/123456789/2926
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Resultados da Pesquisa
Item A construção multimodal de referentes em memes sobre o discurso da pós-graduação(2019) Nogueira, Bruno Huann da Silva; Ranieri, Thaís Ludmila da Silva; http://lattes.cnpq.br/9800015399149501; http://lattes.cnpq.br/4491947961116486Positioning itself in a sociocognitive and multimodal view, the present work aims to investigate how the multimodal construction of meme referents about postgraduate discourse occurs. This study befalls for two reasons, in particular, the first because we believe that the meme genre needs further investigations that seek to understand the complexity of this object, as well as the fact that this genre is a productive space for scientific investigation in the field of language. Thus we discuss in this paper considerations about notions of text, referenciation and multimodality that are based on the discussions of Cavalcante (2013); Cavalcante and Custódio Filho (2010); Koch (2009); Marcuschi (2007 and 2012); Custodio Filho and Hissa (2018); Custódio Filho (2009); Mondada and Dubois (2003); Cavalcante, Filho and Brito (2014); Cortez and Koch (2013); Ranieri (2015); Dionísio (2014); Silva (2018); Vieira and Silvestre (2015); Ramos (2012). Therefore, our approach can be defined as qualitative, since our research seeks to understand, describe and interpret the phenomena linked to referential processes. For this investigation, we had 5 memes that were collected on the Instagram social network between August and October 2019th, in the Mestrado Arrombado page that targets postgraduate publications. Finally, our results show that referents are taken up mainly by Direct Anaphora in the imagery elements that make up memes. Moreover, we also observed that, in most cases, the references "master" and "dissertation" are referenced with a negative value load.Item Comitê de classificador para mineração de opinião de eleitores brasileiros(2019) Souza, Guilherme Henrique Pereira de; Souza, Ellen Polliana Ramos; http://lattes.cnpq.br/6593918610781356; http://lattes.cnpq.br/2474970020729937The recent and exponential growth of social media and user-generated content on the Internet, provide a wealth of data to uncover the feelings, opinions, and experiences of users and customers. Among the various social media currently available, Twitter stands out, with more than 336 million monthly active users. Understanding what people are thinking or their opinions is critical to decision making, especially in the context in which these people express their comments voluntarily. For this type of analysis, opinion mining is used, also known as sentiment analysis, which analyzes people’s opinions, feelings and emotions about entities such as services, products, brands, individuals, problems, events and topics, be expressed in an unstructured form, as in texts, for example. The spread of social media also raises the possibility of delving deeper into the web to explore and track citizens’ political and electoral preferences. In this sense, recent studies explore social media as a device to assess the popularity of politicians during the campaign. Analyzing social media during an election campaign can be a useful supplement or supplement to traditional surveys, and among the reasons include the low cost and speed of real-time analysis. This paper aims to analyze the efficiency of a ensemble for opinion mining applications, using data extracted from Brazilian voters. In this study, an application of opinion mining was developed at the document level using ensembles, with the objective of analyzing the efficiency of the ensembles in such applications. For that, data extracted from Twitter containing opinions of Brazilian voters were used. Six pre-processing configurations and three ensemble approaches were evaluated: Voting, Bagging and Boosting. The results were obtained in terms of Accuracy. According to the experiments, configuration 3, which uses stopwords, n-gram and TF-IDF, achieved the best results, with a 90.26% accuracy for the committee that used the Boosting approach.Item Uma análise dos fenômenos da fala em conversas no WhatsApp(2019) Gois, Aline Raquel Sena de; Ranieri, Thaís Ludmila da Silva; http://lattes.cnpq.br/9800015399149501In this work, we propose to analyze the connection between the speech and the writing in WhatsApp messages, intending to identify speech phenomena in light of the various linguistic theories emerged from Textual Linguistics, in manifestations arisen from everyday interactions in conversations in the environment of the WhatsApp application. In this way, our observations started from the amplified conception about what is a text, under the current ways in which we relate to writing, made possible by the internet through technological resources. The choice of our research locus is justified by its approximation to characteristics of the oral genre, spontaneous conversation arisen from the use of its available tools, giving us a potential corpus for our analyses. In this way, we intend to analyze, with an amplified look to the limit of text, the characteristics of both uses of the language, from which the current theories pull away the dichotomous perspective, making us recognize spoken text construction activities. Therefore, we will be attentive to the recurrences of which the participants rely on to build meanings in the speech events in WhatsApp conversations. For this purpose, we have the technical support of Koch (2006; 2009, 2013), Marcuschi (2007), Cavalcante e Custódio Filho (2010), Fonseca (2011), Cavalcante (2013), Fonte e Caiado (2014), Barbosa (2016), Pereira Lima Carvalho e Acioli (2017) and Oliveira (2018). The corpus of our work was gathered from WhatsApp conversations’ screenshots, from three distinct group chats which are a working-environment group chat which conversations are intended to be more limited to business-related matters; a group chat of friends with unconstrained chat themes, and a group chat with a private contact. In the period of gathering information, we dedicated to observe the interactions between speakers, verifying that the speech and the writing maintain a relation in the crisscross of its characteristics, such as the formality and informality levels of the interactions, which influence these interactions’ dynamics, the writing, the topical progression, the answer time, among other aspects that enabled us to identify speech marks in WhatsApp conversations, as we will prove in the course of our work.