Classifying Product Reviews from Balanced Datasets for Sentiment Analysis and Opinion Mining

Periakaruppan Sudhakaran; Shanmugasundaram Hariharan; Joan Lu

doi:10.1109/MulGraB.2014.14

Classifying Product Reviews from Balanced Datasets for Sentiment Analysis and Opinion Mining

Periakaruppan Sudhakaran, Shanmugasundaram Hariharan, Joan Lu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Citations (Scopus)

Abstract

The Online reviews provided for a product enables web user to make decisions appropriately. These reviews may be positive, negative or neutral in nature. Analyzing and classifying such product reviews have attracted reasonable interest. It has become quite hard to make decisions since we aren't able to obtain the decisions quickly. Hence it is required to classify the reviews from balanced data sets for analysis and opinion mining of any applications. The reason for considering balanced data sets is that the decision will not be biased on the category of reviews considered. We have carried out investigations using similarity measures to categorize the reviews correctly. Experiments reveal that the reviews that were mixed in nature were able to be grouped correctly.

Original language	English
Title of host publication	Proceedings - 6th International Conference on Multimedia, Computer Graphics and Broadcasting, MulGraB 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	29-34
Number of pages	6
ISBN (Electronic)	9781479977642
DOIs	https://doi.org/10.1109/MulGraB.2014.14
Publication status	Published - 27 Jan 2015
Event	6th International Conference on Multimedia, Computer Graphics and Broadcasting - Hainan, China Duration: 20 Dec 2014 → 23 Dec 2014 Conference number: 6 http://www.conferen.org/MulGraB2014/ (Link to Conference Website )

Conference

Conference	6th International Conference on Multimedia, Computer Graphics and Broadcasting
Abbreviated title	MulGraB 2014
Country/Territory	China
City	Hainan
Period	20/12/14 → 23/12/14
Internet address	http://www.conferen.org/MulGraB2014/ (Link to Conference Website )

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10.1109/MulGraB.2014.14Licence: Other

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Sudhakaran, P., Hariharan, S., & Lu, J. (2015). Classifying Product Reviews from Balanced Datasets for Sentiment Analysis and Opinion Mining. In Proceedings - 6th International Conference on Multimedia, Computer Graphics and Broadcasting, MulGraB 2014 (pp. 29-34). [7024252] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MulGraB.2014.14

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abstract = "The Online reviews provided for a product enables web user to make decisions appropriately. These reviews may be positive, negative or neutral in nature. Analyzing and classifying such product reviews have attracted reasonable interest. It has become quite hard to make decisions since we aren't able to obtain the decisions quickly. Hence it is required to classify the reviews from balanced data sets for analysis and opinion mining of any applications. The reason for considering balanced data sets is that the decision will not be biased on the category of reviews considered. We have carried out investigations using similarity measures to categorize the reviews correctly. Experiments reveal that the reviews that were mixed in nature were able to be grouped correctly.",

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author = "Periakaruppan Sudhakaran and Shanmugasundaram Hariharan and Joan Lu",

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Sudhakaran, P, Hariharan, S & Lu, J 2015, Classifying Product Reviews from Balanced Datasets for Sentiment Analysis and Opinion Mining. in Proceedings - 6th International Conference on Multimedia, Computer Graphics and Broadcasting, MulGraB 2014., 7024252, Institute of Electrical and Electronics Engineers Inc., pp. 29-34, 6th International Conference on Multimedia, Computer Graphics and Broadcasting, Hainan, China, 20/12/14. https://doi.org/10.1109/MulGraB.2014.14

Classifying Product Reviews from Balanced Datasets for Sentiment Analysis and Opinion Mining. / Sudhakaran, Periakaruppan; Hariharan, Shanmugasundaram; Lu, Joan.

Proceedings - 6th International Conference on Multimedia, Computer Graphics and Broadcasting, MulGraB 2014. Institute of Electrical and Electronics Engineers Inc., 2015. p. 29-34 7024252.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The Online reviews provided for a product enables web user to make decisions appropriately. These reviews may be positive, negative or neutral in nature. Analyzing and classifying such product reviews have attracted reasonable interest. It has become quite hard to make decisions since we aren't able to obtain the decisions quickly. Hence it is required to classify the reviews from balanced data sets for analysis and opinion mining of any applications. The reason for considering balanced data sets is that the decision will not be biased on the category of reviews considered. We have carried out investigations using similarity measures to categorize the reviews correctly. Experiments reveal that the reviews that were mixed in nature were able to be grouped correctly.

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Classifying Product Reviews from Balanced Datasets for Sentiment Analysis and Opinion Mining

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