JOURNAL ARTICLE

Sentiment Analysis of Tweets Using Various Machine Learning Techniques

Ankit TariyalSachin GoyalNeeraj Tantububay

Year: 2018 Journal:   2018 International Conference on Advanced Computation and Telecommunication (ICACAT) Pages: 1-5

Abstract

In todays e-commerce market where online shopping and tourism is fastly growing so it very important to analyze such huge amount of large data present in web. So it is very important to create a method which classify the web data. Sentiment analysis is a method to classify the web data such as product reviews, views in to various polarities such a positive, negative or neutral. In this paper we classify the reviews by using various machine learning techniques, In this we create a various classification model and compute the performance of each models and select the best classification models based on their performance computation. We will use a combination of simple linear method (LDA), nonlinear methods (CART, KNN) and complex nonlinear methods (SVM, RF, C5.0).

Keywords:
Computer science Sentiment analysis Support vector machine Machine learning Artificial intelligence Computation Data mining Product (mathematics) Data modeling Simple (philosophy) Algorithm Database Mathematics

Metrics

16
Cited By
0.21
FWCI (Field Weighted Citation Impact)
9
Refs
0.58
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Spam and Phishing Detection
Physical Sciences →  Computer Science →  Information Systems
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