No abstract

Bilingualism is the philosophy of choice for deaf education and literacy: deaf children should learn Sign Language for intellectual development, and the written form of the oral language. Unfortunately, educators are still influenced by the clinical view of deafness as a deficiency to be removed, and that view influences their pedagogical praxis that lack proper pedagogical tools. Additionally, there has been a political setback: special schools for the deaf in Brazil are being closed. Mainstream schools are not able to cope with the demands and the deaf are thus further marginalized. This research presents a pedagogical framework that educators have used successfully to prepare classroom-teaching materials. The framework was implemented into a system that guides educators in the design of Learning Objects.

This paper presents a novel approach to perform sentiment analysis of news videos, based on the fusion of audio, textual and visual clues extracted from their contents. The proposed approach aims at contributing to the semiodiscoursive study regarding the construction of the ethos (identity) of this media universe, which has become a central part of the modern-day lives of millions of people. To achieve this goal, we apply state-of-the-art computational methods for (1) automatic emotion recognition from facial expressions, (2) extraction of modulations in the participants' speeches and (3) sentiment analysis from the closed caption associated to the videos of interest. More specifically, we compute features, such as, visual intensities of recognized emotions, field sizes of participants, voicing probability, sound loudness, speech fundamental frequencies and the sentiment scores (polarities) from text sentences in the closed caption. Experimental results with a dataset containing 520 annotated news videos from three Brazilian and one American popular TV newscasts show that our approach achieves an accuracy of up to 84% in the sentiments (tension levels) classification task, thus demonstrating its high potential to be used by media analysts in several applications, especially, in the journalistic domain.

No abstract

ResumoEste artigo aborda a criação de um método computacional baseado em dicionário léxico, que seja capaz de analisar textos em idioma português brasileiro e de polarizar as palavras de acordo com os sentimentos por elas transmitidos. O estudo realizado visa detectar os sentimentos expressos nos textos da Web e comparar a abordagem proposta com métodos existentes, utilizando a aplicação iFeel, que retorna os resultados dos principais métodos para a análise de sentimentos textuais. Pode-se concluir que, por meio de experimentos em uma base de dados do Twitter em português brasileiro, o método proposto retorna os sentimentos associados nos textos analisados com uma acurácia melhor do que os métodos descritos em trabalhos relacionados.Palavras-chave: Análise de Sentimentos. Dicionário Léxico. Método Léxico.⇤ Submetido em 15/02