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Study on Distinct Approaches for Sentiment Analysis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 111 - Number 17 |
| Year of Publication: 2015 |
| Authors: Rupali P. Jondhale, Manisha P. Mali |
10.5120/19758-1487
|
Rupali P. Jondhale, Manisha P. Mali . Study on Distinct Approaches for Sentiment Analysis. International Journal of Computer Applications. 111, 17 ( February 2015), 21-24. DOI=10.5120/19758-1487
Abstract
Now-a-days many researchers work on mining a content posted in natural language at different forums, blogs or social networking sites. Sentiment analysis is rapidly expanding topic with various applications. Previously a person collect response from any relatives previous to procuring an object, but today look is different, now person get reviews of many people on all sides of world. Blogs, e-commerce sites data consists number of implications, that expressing user opinions about specific object. Such data is pre-processed then classified into classes as positive, negative and irrelevant. Sentiment analysis allows us to determine view of public or general users feeling about any object. Two global techniques are used: Supervised Machine-Learning and Unsupervised machine-learning methods. In unsupervised learning use a lexicon with words scored for polarity values such as neutral, positive or negative. Whereas supervised methods require a training set of texts with manually assigned polarity values. This suggest one direction is make use of Fuzzy logic for sentiment analysis which may improve analysis results.
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