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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Sentiment Classification Based on Phonetic Characteristics
verfasst von : Sergei Ermakov, Liana Ermakova
Erschienen in: Advances in Information Retrieval
Verlag: Springer Berlin Heidelberg
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The majority of sentiment classifiers is based on dictionaries or requires large amount of training data. Unfortunately, dictionaries contain only limited data and machine-learning classifiers using word-based features do not consider part of words, which makes them domain-specific, less effective and not robust to orthographic mistakes. We attempt to overcome these drawbacks by developing a context-independent approach. Our main idea is to determine some phonetic features of words that could affect their sentiment polarity. These features are applicable to all words; it eliminates the need to continuous manual dictionary renewal. Our experiments are based on a sentiment dictionary for the Russian language. We apply phonetic features to predict word sentiment based on machine learning.