Learning Word Vectors for Sentiment Analysis
work introduces extensions of LDA to capture sen-timent in addition to topical information (Li et al., 2010; Lin and He, 2009; Boyd-Graber and Resnik, 2010). Like LDA, these methods focus on model-ing sentiment-imbued topics rather than embedding words in a vector space. Vector space models (VSMs) seek to model words directly (Turney and Pantel ...
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