Sentiment Analysis of Document Based on Annotation
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International Journal of Web & Semantic Technology (IJWesT)
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ISSN : 0975 - 9026 ( Online ) 0976- 2280 ( Print )
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Sentiment Analysis of Document Based on Annotation
Authors
Archana Shukla, Motilal Nehru National Institute of Technology, India
Abstract
I present a tool which tells the quality of document or its usefulness based on annotations. Annotation may include comments, notes, observation, highlights, underline, explanation, question or help etc. comments are used for evaluative purpose while others are used for summarization or for expansion also. Further these comments may be on another annotation. Such annotations are referred as meta-annotation. All annotation may not get equal weightage. My tool considered highlights, underline as well as comments to infer the collective sentiment of annotators. Collective sentiments of annotators are classified as positive, negative, objectivity. My tool computes collective sentiment of annotations in two manners. It counts all the annotation present on the documents as well as it also computes sentiment scores of all annotation which includes comments to obtain the collective sentiments about the document or to judge the quality of document. I demonstrate the use of tool on research paper
Keywords
Sentiment Analysis, Opinion Mining, Classification, Annotation, Sentiment Words, Polarity Value
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