alexa Abstract | An Efficient Surveillances of Products Based on Opinion Mining
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article Open Access

Abstract

Sentiment Analysis is a Natural Language Processing and Information Extraction task that aims to obtain writer‟s feelings expressed in positive or negative comments, questions and requests, by analysing a large numbers of documents. Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall totality of a document. In recent years, the exponential increase in the Internet usage and exchange of public opinion is the driving force behind Sentiment Analysis today. The Web is a huge repository of structured and unstructured data. The analysis of this data to extract latent public opinion and sentiment is a challenging task. Sentiment analysis is a technique to classify people‟s opinion in product reviews, blogs or social networks. It has different usages and has received much attention from researchers. In this study, we are interested in product feature based emoticons in sentiment analysis. In other words, we are more interested in identifying the opinion polarities (positive, neutral or negative) expressed on product features. This is termed as the product feature based sentiment analysis. Sentiment Analysis can be performed on both supervised and unsupervised dataset. Sentiment Analysis identifies the phrases and emoticons in a text that bears some sentiment. The sentiment can be objective facts or subjective opinions. It is necessary to distinguish between the two. It identifies the polarity and degree of the sentiment. Sentiments are classified as objective (facts), positive (denotes a state of happiness, bliss or satisfaction on part of the writer) or negative (denotes a state of sorrow, dejection or disappointment on part of the writer). The sentiments can further be given a score based on their degree of positivity, negativity or neutral. Whenever emoticons are used, their associated sentiment dominates the sentiment conveyed by text and forms a good proxy for intended sentiments.

To read the full article Peer-reviewed Article PDF image | Peer-reviewed Full Article image

Author(s): Meenambigai B

Keywords

Blog Data, Feature Extraction, Emoticons, Type of opinion, Oticon

Share This Page

Additional Info

Loading
Loading Please wait..
 
 
Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
adwords