Domain Adaptation in Sentiment Analysis of Twitter
نویسندگان
چکیده
• Sentiment Analysis (SA) requires large human labeled data; which is costly to obtain. • Domain Adaptation(DA) techniques help in performing SA with minimum human labeled data. • Two techniques, Feedback EM and Rocchio SVM are proposed for data selection/filtering. • Use of Mutual Information(MI) and Cosine Distance(CD) to measure similarity between In and Out-Domain distributions.
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