Hierarchical Classification Approach to Emotion Recognition in Twitter
Published 1 December 2012
Ahmed Ali Abdalla Esmin, Roberto Oliveira, Stan Matwin
Citations33
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TL;DR
A novel approach for automatically classifying the sentiment and emotions of Twitter messages is applied and it is shown that the proposed method outperforms the corresponding flat approach in emotion classification.
Abstract
Twitter is a micro logging service where worldwide users publish and share their feelings. However, sentiment analysis for Twitter messages ('tweets') is regarded as a challenging problem because tweets are short and informal. In this paper, we apply a novel approach for automatically classifying the sentiment and emotions of Twitter messages. These messages are hierarchically categorized on basis of neutrality, polarity (positive or negative) and presence of various emotions. The hierarchical classification approach (HC) is a specialization of the well-known flat classification task. The main difference between them is that when using HC, examples must be assigned to classes organized in a previously defined class hierarchy, while traditional flat classification does not take into account the hierarchical information. We applied our model to posts collected from Twitter regarding the 2011 season of the Brazilian Soccer League. Our results show that the proposed method outperforms the corresponding flat approach in emotion classification.
Keywords
Computer Science
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