Caio Jeronimo


2020

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Aspect Flow Representation and Audio Inspired Analysis for Texts
Larissa Vasconcelos | Claudio Campelo | Caio Jeronimo
Proceedings of the Twelfth Language Resources and Evaluation Conference

For better understanding how people write texts, it is fundamental to examine how a particular aspect (e.g., subjectivity, sentiment, argumentation) is exploited in a text. Analysing such an aspect of a text as a whole (i.e., through a summarised single feature) can lead to significant information loss. In this paper, we propose a novel method of representing and analysing texts that consider how an aspect behaves throughout the text. We represent the texts by aspect flows for capturing all the aspect behaviour. Then, inspired by the resemblance between these flows format and a sound waveform, we fragment them into frames and calculate an adaptation of audio analysis features, named here Audio-Like Features, as a way of analysing the texts. The results of the conducted classification tasks reveal that our approach can surpass methods based on summarised features. We also show that a detailed examination of the Audio-Like Features can lead to a more profound knowledge about the represented texts.