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A Review on Opinion Mining Techniques and Challenges

IJCA Proceedings on National Conference on Advances in Computing Applications
© 2016 by IJCA Journal
NCACA 2016 - Number 2
Year of Publication: 2016
Nikita Bansal
Prashant Pandey
Aprna Tripathi

Nikita Bansal, Prashant Pandey, Banti and Aprna Tripathi. Article: A Review on Opinion Mining Techniques and Challenges. IJCA Proceedings on National Conference on Advances in Computing Applications NCACA 2016(2):4-7, September 2016. Full text available. BibTeX

	author = {Nikita Bansal and Prashant Pandey and Banti and Aprna Tripathi},
	title = {Article: A Review on Opinion Mining Techniques and Challenges},
	journal = {IJCA Proceedings on National Conference on Advances in Computing Applications},
	year = {2016},
	volume = {NCACA 2016},
	number = {2},
	pages = {4-7},
	month = {September},
	note = {Full text available}


With the evolution of web technology, there is a huge amount of data present in the web for the internet users who uses almost every available data for one to another usage in their day to day life. These users not only use data but also give their opinion in the form of feedback, thus generating additional useful information. By these user's opinions, views, feedback and suggestions available, it become really useful to explore, analyse and organize their views for better decision making. Nowdays,Merchants selling product on the web often ask their customers to review the products that they have purchased. As E-Commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. This makes it difficult for a customer to read them to make a decision on whether to purchase the product. In this research, we aim to mine and to summarize all the customer reviews of a product. And this summarization task involves the mining of the features of the product on which the customers have expressed their opinion on whether the opinions are positive or negative. This workflow of reviews is facilitated by a technique called Opinion Mining. Opinion itself means "what other people think"and mining illustrates "opinions explained in the form of positive, negative or neutral comments and quotes underlying the text". This survey gives an overview of the efficient techniques which can be implemented, discuss about the applications, recent as well as future challenges yielding in the field of opinion mining and about tools which are used to track the opinion or polarity from user generated contents.


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