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Traditional affective lexicons are mainly based on discrete classes, such as positive, happiness, sadness, which may limit its expressive power compared to the dimensional representation in which affective meanings are expressed through continuous numerical values on multiple dimensions, such as valence-arousal. Traditional methods for acquiring dimensional lexicons are mainly based on time-consuming...
Automatic sentiment information extraction of social network articles has many essential applications. Following the valence-arousal space framework, in this paper, two approaches including (1) a weighted graph (WG) and (2) a neural network (NN) model that could predict the valence-arousal ratings of words are evaluated on the Chinese valence-arousal words (CVAW) database provide by the IALP-2016...
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