John Violos
Konstantinos Tserpes
ABSTRACT
The Word-Graph Sentiment Analysis Method is proposed to identify the sentiment that expressed in a microblog document using the sequence of the words that contains. The sequence of the words can be represented using graphs in which graph similarity metrics and classification algorithms can be applied to produce sentiment predictions. Experiments that were carried out with this method in a Twitter dataset validate the proposed model and allow us to further understand the metrics and the criteria that can be applied in words-graphs to predict the sentiment disposition of short, microblog documents.
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