Sentiment Analysis - Methods, Applications & Challenges

Ms. Swati B. Bhonde; Prof. Jayashree R. Prasad

With the excogitation of World Wide Web, Internet has become a coercive platform for people to express their views, opinions, emotions and sentiments about particular product, people and about life in general. So, when anyone wants to buy some product they prefer to go through several user reviews, blogs and discussion available in public forums. This opinionated textual data & word of mouth represents new & measurable source of information in many applications. Due to increased availability of online reviews in digital form, need to organize them in proper structured format is becoming necessary. Sentiment Analysis (SA) is one of the most widely studied applications in the era of Natural Language Processing (NLP) & Machine Learning (ML) which deals with identifying & extracting essential information from public opinion. This helps to make better decision in business intelligence, political campaigns & in product recommendation system. This paper presents survey on Sentiment Analysis, methods, applications and challenges. This review discusses methods for feature selection & sentiment classification in detail which will prove helpful for user in sentiment classification.

Select Volume / Issues:

• Volume 6,Issue 6, Nov. 2015

Year:

2015

Type of Publication:

Article

Keywords:

Sentiment Analysis SA; Natural Language Processing NLP; Opinion Mining OM; Machine Learning ML; Latent Semantic Indexing LSI

Journal:

IJECCE

Volume:

6

Number:

6

Pages:

634-640

Month:

November