Multi-Classifier based Sentiment Analysis for Opinionated Data Posted in Social NetworkingJournal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.9, No. 12)
Publication Date: 2020-12-30
Authors : Partha Sarker; Siddhartha Roy;
Page : 68-75
Keywords : Opinion mining; Sentiment analysis; sentiment target; Emotion analysis;
Huge quantities of information are available through web and social media platforms have made available to users worldwide. Social networking is the most valuable source of learning, getting ideas, reviews for a product or a service. Everyday millions of users post view about a product, person or a place, give their views, ideas on blog, twitter. Ideas use reviews, assessment surveys, and online networking as a device to obtain criticism on their items and services. The web has extremely huge number and size it is very difficult to handle and understand such reviews. Sentiment analysis is an emerging field in the research area is used to analyse and extracts the opinion from the given review and the analysis process includes natural language processing (NLP), computational linguistics, text analytics and classifying the polarity of the opinion. In the field of sentiment analysis there are many algorithms exist to tackle NLP problems. This immense volume of information may forces potential beneficial business related data, which when separated keenly and spoke to sensibly, can be a mine of gold for administrations Research &Development (R&D), attempting to add library an item in light of prominent popular opinion. In this paper, we use the multi-classifier model in the area of Sentiment Analysis using Support Vector Machine which worked on review /opinion posted on social network/ twitter. Our work aims at forfeiting these researches with greater accuracy and potential to excel in both retail and corporate forums.
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