@inproceedings{b874ba07f4314aa097acb280b772908e,
title = "Analyzing sentiment in a large set of web data while accounting for negation",
abstract = "As virtual utterances of opinions or sentiment are becoming increasingly abundant on the Web, automated ways of analyzing sentiment in such data are becoming more and more urgent. In this paper, we provide a classification scheme for existing approaches to document sentiment analysis. As the role of negations in sentiment analysis has been explored only to a limited extent, we additionally investigate the impact of taking into account negation when analyzing sentiment. To this end, we utilize a basic sentiment analysis framework – consisting of a wordbank creation part and a document scoring part – taking into account negation. Our experimental results show that by accounting for negation, precision on human ratings increases with 1.17%. On a subset of selected documents containing negated words, precision increases with 2.23%.",
author = "B.M.W.T. Heerschop and {Iterson, van}, P. and A.C. Hogenboom and F. Frasincar and U. Kaymak",
year = "2011",
doi = "10.1007/978-3-642-18029-3_20",
language = "English",
isbn = "978-3-642-18028-6",
series = "Advances in Intelligent and Soft Computing",
publisher = "Springer",
pages = "195--205",
editor = "E. Mugellini and P.S. Szczepaniak and M.C. Pettenati and M. Sokhn",
booktitle = "Advances in Intelligent Web Mastering - 3 (Proceedings of the 7th Atlantic Web Intelligence Conference, AWIC 2011, Fribourg, Switzerland, January 26-28 2011)",
address = "Germany",
note = "conference; 7th Atlantic Web Intelligence Conference (AWIC 2011); 2011-01-26; 2011-01-28 ; Conference date: 26-01-2011 Through 28-01-2011",
}