Multilingual Support for Lexicon-Based Sentiment Analysis Guided by Semantics.

Alexander Hogenboom, Bas Heerschop, Flavius Frasincar, Uzay Kaymak, Franciska M.G. de Jong

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    83 Citations (Scopus)
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    Many sentiment analysis methods rely on sentiment lexicons, containing words and their associated sentiment, and are tailored to one specific language. Yet, the ever-growing amount of data in different languages on the Web renders multi-lingual support increasingly important. In this paper, we assess various methods for supporting an additional target language in lexicon-based sentiment analysis. As a baseline, we automatically translate text into a reference language for which a sentiment lexicon is available, and subsequently analyze the translated text. Second, we consider mapping sentiment scores from a semantically enabled sentiment lexicon in the reference language to a new target sentiment lexicon, by traversing relations between language-specific semantic lexicons. Last, we consider creating a target sentiment lexicon by propagating sentiment of seed words in a semantic lexicon for the target language. When extending sentiment analysis from English to Dutch, mapping sentiment across languages by exploiting relations between semantic lexicons yields a significant performance improvement over the baseline of about 29% in terms of accuracy and macro-level F1 on our data. Propagating sentiment in language-specific semantic lexicons can outperform the baseline by up to about 47%, depending on the seed set of sentiment-carrying words. This indicates that sentiment is not only linked to word meanings, but tends to have a language-specific dimension as well.
    Original languageUndefined
    Pages (from-to)43-53
    Number of pages11
    JournalDecision support systems
    Issue number1
    Publication statusPublished - Jun 2014


    • EWI-24918
    • Machine translation
    • Multi-lingual sentiment analysis
    • Lexicon
    • Propagation
    • Semantics
    • METIS-305950
    • IR-91769
    • Map

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