Janaína Gomide

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Twitter is a unique social media channel, in the sense that users discuss and talk about the most diverse topics, including their health conditions. In this paper we analyze how Dengue epidemic is reflected on Twitter and to what extent that information can be used for the sake of surveillance. Dengue is a mosquito-borne infectious disease that is a leading(More)
How do we analyze sentiments over a set of opinionated Twitter messages? This issue has been widely studied in recent years, with a prominent approach being based on the application of classification techniques. Basically, messages are classified according to the implicit attitude of the writer with respect to a query term. A major concern, however, is that(More)
A common assumption when collecting network data is that objects can be uniquely identified. However, in many scenarios objects do not have a unique label giving rise to ambiguities since the mapping between observed labels and objects is not known. In this paper we consider the ambiguity problem that emerges when objects appear with more than one label in(More)
In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions(More)
Online social networks are used at a daily basis by millions of users around the world. More and more people use these networks to interact, to issue opinions, and to share content about several different topics, such as entertainment, weather, work, family, traffic, and even their health conditions. In summary, social networks became another social place(More)
Individuals often appear with multiple names when considering large data-sets collected from different sources, giving rise to the name ambiguities. Name ambiguity comes in two flavors: a single individual appearing with more than one name (synonym problem); a single name being used to refer to more than one individual (homonym problem). This works focuses(More)
Individuals often appear with multiple names when considering large bibliographic datasets, giving rise to the synonym ambiguity problem. Although most related works focus on resolving name ambiguities, this work focus on classifying and characterizing multiple name usage patterns—the root cause for such ambiguity. By considering real examples bibliographic(More)
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