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Knowledge and Information Systems
Published in: Knowledge and Information Systems 3/2017

10-05-2017 | Regular Paper

Document-level sentiment classification using hybrid machine learning approach

Authors: Abinash Tripathy, Abhishek Anand, Santanu Kumar Rath

Published in: Knowledge and Information Systems | Issue 3/2017

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Abstract

It is a practice that users or customers intend to share their comments or reviews about any product in different social networking sites. An analyst usually processes to reviews properly to obtain any meaningful information from it. Classification of sentiments associated with reviews is one of these processing steps. The reviews framed are often made in text format. While processing the text reviews, each word of the review is considered as a feature. Thus, selection of right kind of features needs to be carried out to select the best feature from the set of all features. In this paper, the machine learning algorithm, i.e., support vector machine, is used to select the best features from the training data. These features are then given input to artificial neural network method, to process further. Different performance evaluation parameters such as precision, recall, f-measure, accuracy have been considered to evaluate the performance of the proposed approach on two different datasets, i.e., IMDb dataset and polarity dataset.
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Metadata
Title
Document-level sentiment classification using hybrid machine learning approach
Authors
Abinash Tripathy
Abhishek Anand
Santanu Kumar Rath
Publication date
10-05-2017
Publisher
Springer London
Published in
Knowledge and Information Systems / Issue 3/2017
Print ISSN: 0219-1377
Electronic ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-017-1055-z

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