Learning to Construct a Context-Aware Sentiment Lexicon

As the influence of online reviews on buying decisions has grown, research interests on mining opinions for determining the polarity of a document have increased. Previous lexicon-based methods of sentiment analysis pay less attention to the fact that the context may change word polarity. Given the sentiment information of documents in the training data, the goal of this study is to learn different polarity scores for the same word with various contexts. The experiments have been conducted on the real data sets in three domains. The results of the experiments demonstrate the feasibility of the proposed method.