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Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/1997

Title: Improving the Lexicon of Positive/Negative Words and Bigrams for Sentiment Analysis
Authors: Tsonkov, Todor
Koychev, Ivan
Keywords: извличане на мнения от текст
списък от положителни и отрицателни думи
Issue Date: 31-May-2013
Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences, Association for the Development of the Information Society
Citation: Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013, 268p-273p
Series/Report no.: ADIS;2013
Abstract: Тhe idea of the current paper is to propose an algorithm for improving the list of positive and negative words based on a specific topic. The opinions are classified by a person or a machine (or combined) and the most frequent words are being found that are not in the list of stop words. These words are being added to the list and than with a sample classifier is found improvement in the classification of the already exctracted opinions. Several tests have been described to show how to test the algorithm.
Description: Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013
URI: http://hdl.handle.net/10525/1997
ISSN: 1314-0752
Appears in Collections:ADIS 2013

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