Title Of Paper:
 
 
Sentiment Mining on Products Features based on Part of Speech Tagging Approach
Author's Name :  Mohadese Abedi Shahkhali, Fatemeh Ahmadi-Abkenari
KeyWords:  Opinion mining, Sentiment mining, Subjective and objective sentences, Text mining.
Pages:  1 -12
Volume: 3
Issue: 12
Year: 2015
Abstract:
 

In today's competitive businesspaying attention to the feedback fromcustomers has become a valuable factor for organizations.Organizations have found that satisfied customers are not only a repeated buyer, they are also propaganda arm of the organization.Therefore, the correct analysis of their feedback by relying on information technology tools is a key element in the success of the organizations in trade. People generally share their opinions about purchased goods on the Web sites or in social networks. Extraction of these opinions is known as a special branch of text mining under the term of sentiment mining. Although this category is brand new, but in recent years, extensive researches have been done on sentiment analysis and classification of intentions. Therefore, in this paper a model is suggested about sentiment mining with the ability to extract users opinion and product features. So dataset of customer comments has been made in a way that the comments are taken from a Website about some specific digital products. Then the paragraphed opinions are converted into sentences and the sentences are separated into two categories of subjective and objective. Next, user's opinion and product features are taken from subjective sentences by using StanfordPOStagger and relying on Tf-idf factor for product features and finding opinion polarity by using SentiWordNet tools. In this way, user satisfaction of specific features of the product can be detected. As a means of evaluation, three factors of Recall, Precision and F-Measureprovide an indication of the accuracy of each part of this research.

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