A Survey on Sentiment Classification and Analysis using Data Mining
Main Article Content
Abstract
Sentiment analysis is a type of natural language processing that tracks the opinion and mood of the public about the specific product. The volume of information in digital form increases day-by-day as people express their sentiments, also called opinions everywhere mostly on internet as the people now days are much dependent on internet. So the requirement of user opinions analysis is gaining importance day by day. Blogs, micro blogs, review sites, twitter, and other social networks are the most common platforms that are used by people and organizations for posting their views. Researchers has done very immense effort in the field of sentiment analysis and also new opportunities and challenges still arise so even now it is very active and dynamic research area in the field of natural language processing. It is also widely investigated in text mining, data mining and web mining. This paper attempts to evaluate the several techniques used for sentiment analysis. The goal of this survey is to give an in-depth introduction to this fascinating problem and to present a comprehensive study of all important research using data mining and the latest developments in the field.
Keywords: Opinion Mining, NLP, Sentiment Analysis, Information Retrieval, Naïve Bayes Algorithm
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.