Improving sentiment classification accuracy of financial news using n-gram approach and feature weighting methods

Improving sentiment classification accuracy of financial news using n-gram approach and feature weighting methods

Sentiment classification of financial news deals with the identification of positive and negative news so that they can be applied in decision support system to perform stock trend predictions. This paper explores several types of feature space as different datasets for sentiment classification of t...

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Bibliographic Details
Main Authors: Yazdani, Sepideh Foroozan, Azmi Murad, Masrah Azrifah, Mohd Sharef, Nurfadhlina, Abdul Latiff, Ahmed Razman
Format: Conference or Workshop Item
Language:English
Published: IEEE 2015
Online Access:http://psasir.upm.edu.my/id/eprint/14342/
http://psasir.upm.edu.my/id/eprint/14342/1/Improving%20sentiment%20classification%20accuracy%20of%20financial%20news%20using%20n-gram%20approach%20and%20feature%20weighting%20methods.pdf

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