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Paper Title: Overall Sentiment Analysis In One Go Using Supervised Joint Aspect Sentiment Model
Authors Name: Sai Nikhil Reddy Gudibandi , Priyanka Reddy
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Published Paper Id: IJNRD1804027
Published In: Volume 3 Issue 4, April-2018
Abstract: This journal mainly focussed on analysing reviews generated by the user and it also identifies aspect-level sentiments from the review data as well as predicts overall sentiments of the reviews.this prediction is done by forming opinion pairs which are set of aspect term and opinion word. Here we used SJASM model over the already existing LDA model , which helps in detecting overall analysis in one go. SJASM can find out hidden sentiment analysis by using aspect-level analysis. It not only predicts the overall analysis of the document but also gives the user the extra advantage of aspect level sentiment analysis where every aspect is been looked into.
Keywords: Sentiment analysis, aspect-based sentiment analysis, probabilistic topic model, supervised joint topic model.
Cite Article: "Overall Sentiment Analysis In One Go Using Supervised Joint Aspect Sentiment Model", International Journal of Novel Research and Development (, ISSN:2456-4184, Vol.3, Issue 4, page no.146-148, April-2018, Available :
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