Sentiment Analysis and Opinion Mining: A Survey

Abstract

Opining mining has gained high level focus in business and commercial fields. The opinions are considered as valuable data. Opinions are customer reviews, comments and feelings and collected from web forums, websites, and user groups which are posted by thousands of end users and also recorded manually. The collected opinions are processed by various techniques, algorithms, methods and software tools in order to extract the meaning from them. Extraction of meaningful information from opinions is given more importance in the field of business analytics. This entire process is popularly known as opinion mining or sentiment analysis and they are used in industries to develop quality of services, products. This article is an outcome of a study which made on various sub tasks, approaches, methods and techniques involved and applied in opinion mining.

Impact analysis of adverbs for sentiment classification on Twitter product reviews

“…Some researchers have used only one feature, while others have used different combinations for classification. Alhojely 15 in 2016 conducted a survey on sentiment analysis and highlighted the importance of sentiment classification, its tools, and techniques available. Classification of user reviews as negative and positive using only one feature from verbs, noun, adjectives, and adverbs is a challenging task for researchers.…”

Different Applications and Techniques for Sentiment Analysis

“…The order techniques that utilization ML approach can be separated into Supervised and Unsupervised learning strategy. The Lexicon-construct approach depends in light of supposition vocabulary [19]. Dictionary considers as an imperative pointer for supposition, which called conclusion word.…”