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Negation Identification and Calculation in Sentiment Analysis

Authors:
Amna Asmi
Tanko Ishaya

Keywords: Negation Identification; Negation Calculation; Subjectivity Analysis; Sentiment Analysis; Opinion Mining; Social Media Mining; Text Mining

Abstract:
The extensive growth of user-generated content has introduced new aspects of analysis on World Wide Web data. Sentiment analysis of written text on the web is one of the text mining aspects used to find out sentiments in a given text. The process of sentiment analysis is a task of detecting, extracting and classifying opinions and sentiments expressed in texts. It includes the identification of the meaning of words within the text through natural language processing rules. While existing research presents a number of approaches for sentiment analysis, these approaches have not quite provided an appropriate and efficient way of calculating and representing the role of negation in sentiment analysis. Therefore, this paper presents a framework for automatic identification of the presence of opinion in textual data. The proposed framework includes a description of rules for negation identification and calculation. These negation rules are designed in order to improve sentiment text analysis. Main achievement of the paper is a demonstration on an approach for automatic identification and calculations of negation in opinion and sentiment analysis.

Pages: 1 to 7

Copyright: Copyright (c) IARIA, 2012

Publication date: October 21, 2012

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-227-1

Location: Venice, Italy

Dates: from October 21, 2012 to October 26, 2012