Survey of sentiment analysis and its impact on data extraction

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Published Sep 8, 2021
Narahari Ajmeera Dr. P. Kamakshi Dr. B. Vishnu Vardhan

Abstract

With the advent of information exploration over the years, the most important thing to make the business decision is to consider the opinion of the peoples. Sometimes the opinions which are transformed to sentiments plays a vital role in the aforementioned areas. The opinion of the people is shared by the e-commerce, social media networks like twitter, facebook, blogs, forums, and etc., The opinion is categorized into positive, negative and neutral opinion. To extract the sentiments, opinions there are different approaches available in the literature such as support vector machine, Naïve Bayes, Neural Networks, N-gram, lexicon based approaches [12-15] etc. In this paper it is aimed at comparing different type of machine learning approaches such as supervised [7], unsupervised and semi supervised learning algorithms which are useful to extract the various opinions over the Net. It is further surveyed to understand various performance measures when the extracted opinions were transformed to sentiments.

How to Cite

Ajmeera, N., P, K., & B, V. V. (2021). Survey of sentiment analysis and its impact on data extraction. SPAST Abstracts, 1(01). Retrieved from https://spast.org/techrep/article/view/199
Abstract 17 |

Article Details

Keywords

Machine Learning, NLP tools, Natural Language Processing (NLP), Sentiment Analysis

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Section
GE3- Computers & Information Technology