Improving Opinion Target Identification through Twitter Using Public Conversations
Abstract
In this paper, we propose a new method for opinion target identification based on twitter conversations rather than simple individual tweets. We employ conversation interactions to effectively extract the different target features using a product review corpus involving smart-phones and other electronics products. Experimental evaluations show that our proposed method is efficient and contributes to improving system performance.
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