01.1 - Graduação (Sede)
URI permanente desta comunidadehttps://arandu.ufrpe.br/handle/123456789/2
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Resultados da Pesquisa
Item A emoção na música pernambucana e periférica: o amor nos tempos do brega romântico(2024-02-29) Santos, Maria Cecília Duran Correia; Cardoso, Maria Grazia Cribari; http://lattes.cnpq.br/2450643941158970; http://lattes.cnpq.br/9308546036230827Emotions are culturally constructed and historically shaped by the context in which they are embedded, manifesting symbolically through cultural, social, and artistic expressions. Emotions, especially love, are influenced by the cultural context of the society in which they exist, such as gender performance and classes. The article aims to study emotions and analyze the expression of love found in romantic brega music produced in the state of Pernambuco. The study process was conducted through qualitative research, drawing on classical and contemporary theorists of the Anthropology of Emotions. Field research was carried out at brega shows and carnival events. Interviews with listeners were conducted, and some songs were analyzed using interpretative methods. Through this musical style, it is possible to envision a specific cultural field with social and emotional factors embedded in the construction of lyrics, which relate to the perceived meaning of love by both listeners and music producers.Item Confeitaria e saúde mental(2024-03-08) Oliveira, Lucicleide Eliete Pereira de; Siqueira, Amanda de Morais Oliveira; http://lattes.cnpq.br/0925121801904264The word "confectionery" derives from the Latin verb "conficere," related to food preparation. Besides being an ancient practice, confectionery is recognized as a form of occupational therapy, with contemporary studies exploring its relationship with psychological well-being. Mental health, defined as emotional balance and the ability to cope with challenges, is influenced by biological, psychological, and social factors. This work aims to describe the main emotional perceptions reported by the practice of confectionery and analyze personal accounts of the possible emotional effects on confectionery experiences at different production stages. The results of the research on confectionery and mental health, conducted with 103 individuals who answered questions about the psychological effects that making sweet preparations had on their mental health. The sample consisted of valid participants (n=78). The majority of participants (87.2%) reported feeling some positive effect. Participants highlighted several reasons for this, including learning and enjoyment in the product, moments of focus and concentration, therapy and artistic expression, stress relief and fulfillment, positive social effects, female empowerment, and other therapeutic reasons. 88.5% of participants reported an improvement in their mental health through confectionery, 89.4% indicate that this activity can be an effective form of creative therapy; 93.2% of stress and anxiety reduction, and 83.3% reported positive experiences sharing their creations with friends, family, or online communities. Despite the promising results of this research, further investigations are still needed to corroborate and deepen our understanding of the relationship between confectionery and mental health. Additional studies could explore different aspects of this connection, such as the long-term effects of confectionery practice on mental health, the effectiveness of specific confectionery interventions for treating psychological conditions, and the influence of contextual factors, such as the work or social environment, on individuals' experiences.Item Análise de sentimentos dos tweets relacionados ao Superior Tribunal Federal no ano de 2019(2022-11-10) Cadengue, Guilherme Lapa de Araújo; Andrade, Ermeson Carneiro de; Bocanegra, Silvana; http://lattes.cnpq.br/4596111202208863; http://lattes.cnpq.br/2466077615273972; http://lattes.cnpq.br/8502533221842320The Social media since its inception has affected all Internet users. Networks such as Twitter provide a new form of communication, interaction and, above all, a way of expressing opinions about the different events of life in society, consequently enabling the generation of content. Knowing the opinions of Brazilians about public institutions is very important for engaging people in society, as agents participating in decisions that affect all individuals, that is, it is a form of social inclusion. The application of Sentiment Analysis is carried out in several areas in order to extract the content of public opinion. The objective of this work is to identify the feelings of the Brazilian population about the Superior Federal Court of Brazil through the content of published tweets between January and December 2019. For this, the tweets in the period were collected, which were pre-processed, classified and then analyzed. The results show highly polarized opinions, but generally negative opinions regarding the STF are predominant (estimate at 51.7%).Item Análise de sentimentos de tweets relacionados a vacinas antes e durante a pandemia da COVID-19 no Brasil(2023-03-01) Silva, Íkaro Alef de Lima; Andrade, Ermeson Carneiro de; http://lattes.cnpq.br/2466077615273972; http://lattes.cnpq.br/7938306473921402In early 2020, the COVID-19 disease spread rapidly around the world and one of the ways to fight it is the vaccine. Governments faced problems with fake news and anti-vaccination groups. Thus, it is necessary to understand the feelings of the population in order to propose efficient public policies. This article describes a sentiment analysis on vaccine-related tweets in Brazil from June 2020 to June 2021. The results revealed peaks in total tweets in January and May 2021, the predominance of positive tweets, and feelings of confidence, fear, submission and sadness. They are also associated with former President Jair Bolsonaro. The negative polarity was the least common, showing that the Brazilian population was receptive to vaccines.Item Análise de sentimentos em Tweets relacionados ao desmatamento da Floresta Amazônica(2021-12-17) Silva, Vinicius José Paes e; Andrade, Ermeson Carneiro de; http://lattes.cnpq.br/2466077615273972; http://lattes.cnpq.br/7437953784606274The Amazon Forest is being devastated at the fastest pace in recent years. In 2021, the Amazon rainforest registers the largest accumulation of deforestation in 5 years, increasing from 13 thousand km2 between August 2020 and July 2021. An increase of 22% compared to the same period in the previous year, the highest number since 2006. Although many works address the issue of deforestation, none of them focus on analyzing the sentiments of the Brazilian population regarding the issue. This work presents an analysis of the sentiments of the Brazilian population related to the deforestation of the Amazon rainforest through the text mining of Twitter and aims to understand how Brazilian users opine and dialogue about the deforestation of the Amazon rainforest. The results reveal that Brazilian users tend to react to events related to deforestation in the Amazon forest on Twiter and that most users have a negative sentiment about the topic, reaching peaks of approximately 60% of tweets in a given time.Item 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.Item Estudo comparativo de algoritmos de classificação supervisionada para classificação de polaridade em análise de sentimentos(2019) Albuquerque, Rotsen Diego Rodrigues de; Albuquerque Júnior, Gabriel Alves de; http://lattes.cnpq.br/1399502815770584; http://lattes.cnpq.br/6441716676783585The huge increase of data on the Internet, it is a rich source for public opinion assessment of a specific subject. Consequently, the number of opinions available makes decision-making impossible if it is necessary to read and analyze all opinions. Since the use of Machine Learning has been widely used, I will present a comparative study of two algorithms for classifying movie comments using techniques of natural language processing and Sentiment Analysis. The data obtained were obtained manually where through the competition site called Kaggle where we have about 50,000 comments on various films. The purpose of this study is also to use the concepts of data science and Machine Learning, natural language processing and sentiment analysis to add more information about the entertainment and film industry. That is why these algorithms were created so that it is possible to show the results for this domain in the of movies comments registered in one big site/platform of movie industry, the famous IMDB. After training and testing, the machine had an accuracy of 86 % on predicting sentiments on commented text from movies.Item Aspect term extraction in aspect-based sentiment analysis(2019) Francisco, Alesson Delmiro; Lima, Rinaldo José de; http://lattes.cnpq.br/7645118086647340The increasing use of the Internet in many directions has created a necessity to analyze alarge quantity of data. A large amount of data is presented as Natural Language Text,which is unstructured, with many ways to express the same information. It is an importanttask to extract information and meaning from those unstructured content, such as opinionson products or services. The need to extract and analyze the large amount of data createdevery day on the Internet surpassed the capabilities of human ability, as a result, manytext mining applications that extract and analyze textual data produced by humans areavailable today, one of such kind of applications is Sentiment Analysis, viewed as a vitaltask both to the academic and commercial fields, so that companies and service providerscan use that knowledge extracted from textual documents to better understand how theircustomers think about them or to know how their products and services are appreciated ornot by their customers. However, the task of analysing unstructured text is a difficult one,that is why it is necessary to provide coherent information and concise summaries to thoserevisions. Sentiment Analysis is the process of computationally identifying and categorizingopinions expressed in a piece of text, especially in order to determine the writer’s attitudetowards a particular topic or product. Aspect-Based Sentiment Analysis is a sub-field ofSentiment Analysis that aims to extract more refined and exact opinions, by breakingdown text into aspects. Most of the current work in the literature does not take profitof either semantic-based resources or NLP-based analysis in the preprocessing stage. Tocountermeasure these limitations, a study on these resources is done aiming to extract thefeatures needed to execute the task, and to make the best combination for ATE. This workhas the main goal of implementing and analysing a method of Aspect Term Extraction(ATE) of users reviews (restaurants and laptops). The proposed method is based on asupervised approach called Conditional Random Fields (CRF) which is able to optimizethe use of features for classification, this choice was justified by previous related work thatdemonstrate the effectiveness of CRF for ATE. Also, we are investigating the existingmethods and features for ABSA, as well as proposing new features and experimentingwith feature combinations in order to find the best features combinations, that are not yetcovered in the state of art. The detailed study is done by experimenting with word features,n-grams and custom made features using an CRF supervised algorithm to accomplish thetask of Aspect Term Extraction with results in terms of Precision, Recall and F-measure,the standard evaluation metrics adopted in the field. Finally, a comparative assessmentbetween the proposal method for ATE against other related work presented in the literaturehas shown that the method presented by this work is competitive.Item Os efeitos da (in)felicidade no processo dedesenvolvimento de software(2019) Falcão, Tiago Coutinho; Marinho, Marcelo Luiz Monteiro; http://lattes.cnpq.br/3362360567612060; http://lattes.cnpq.br/8796523691341550In the software development process, the main actor responsible for directly impacting production is the individual.With the increase of literature and professional experiences,as well as the importance of studying the human being, recent studies involving the human aspects in software engineering seek to relate psychological factors with exact sciences. Studies show that emotions such as (un) happiness in a software development environment are directly linked to software quality, affecting developer performance.Understanding happiness and unhappiness can be worked out in ways that improve work environment, productivity, and developer motivation. This paper aims to identifythe effects of (un) happiness on the performance of software developers operating in the state of Pernambuco. In this paper, we will analyze the effects and moderating fac-tors that influence the performance of developers when they are happy and un happy during the software development process. Based on a literature review and the opin-ion of those involved in software development, through a questionnaire, which was at-tended by 71 developers, the moderating factors capable of emotionally influencing theindividual leading to the improvement or worsening of their performance were raised.These include: negatively influencing mental and physical health and team motivation as a positive moderating factor.Although some companies have flexibility in many ways such as clothing, coffee breaks and leisure spaces, developer attention is often not explored individually. In this paper, we can conclude that factors such as Mental Health prove that care for the well-being of the individual is extremely important for the proper functioning of the development process.Item Abordagem híbrida e independente de domínio para extração de aspectos na análise de sentimentos(2018) Lins, André Lucas Machado; Lima, Rinaldo José de; http://lattes.cnpq.br/7645118086647340; http://lattes.cnpq.br/3233947254235611Opinions are central in most of the human activities and are keys of influence to our behaviors. Our beliefs, perception of reality and our choices are in a considerable degree, influenced by how people see and evaluate the world. In view of this statement theSentimentAnalysis(SA)hasbeengrowingconstantly,thepossibilityofunderstand people’sfeelingsandopinionsaboutcertainsubjectsgetseveryoneexcited.Sentiment Analysisisthecomputationalstudyofpeople’sopinions,attitudesandemotionsabout some entity. The literature about Sentiment Analysis is pretty wide, having too many ways of execute such tasks. A variation of SA called Aspect based Sentiment Analysis (ABSA) has been receiving researchers attention. In this approach feelings are identified in relation to sentence aspects, in order to discern those that are treated in eachsentenceordocument.ABSAisdividedinthreemajortaskswhicharetheextraction,classificationandaggregationoftheaspect,havingaspectextractionasthemost complextask.There’sseveralapproachestosolvetheaspectextractiontask,although manyoftheseapproachesaredomaindependent,makingdifficulttoreplicatetheseapproaches to domains that does not have the same features. Therefore, this work aims topurposeadomainindependenthybridmethodtoaspectsextraction,thatconsistsin fourmajorsteps.Thefirstoneidentifyallthepossibleaspectsoutofsemanticrulesfor eachsentence.Afterthisstep,willbegeneratedalexicalofallthesentenceshavingthe aspectsandmostrelevantfeelings.Inthefollowstepismadethepruningofpossibleaspectsusingsemanticrulesthroughthelexicalofaspectsandfeelingsmadepreviously. Lastly,ismadeaselectionamongtheremainingaspectsbyadynamicthreshold.This purpose was evaluated in the Semeval’s dataset, containing opinions about several aspects related to restaurants and laptops, using the most adopted evaluation metrics in literature. The experimental results imply that the proposed method is competitive when it’s compared to many other methods dependents and independents of state of art domain.