Rather short but well written and interesting analysis of two smoothing methods for sentiment mining, evaluated on a twitter dataset. Paper is quite dense to to its short length of only 4 pages. The results are comparable or show small improvements over naive approaches without smoothing
Ссылки
Закладки
Рецензия удаляется
Пожалуйста, войдите в систему, чтобы принять участие в дискуссии (добавить собственные рецензию, или комментарий)
Цитировать эту публикацию
%0 Conference Paper
%1 iswcTwitter2011
%A Saif, Hassan
%A He, Yulan
%A Alani, Harith
%B The 10th International Semantic Web Conference (ISWC)
%C Bonn, Germany
%D 2011
%K
%T Semantic Smoothing for Twitter Sentiment Analysis
@inproceedings{iswcTwitter2011,
added-at = {2012-02-29T10:50:09.000+0100},
address = {Bonn, Germany},
author = {Saif, Hassan and He, Yulan and Alani, Harith},
biburl = {https://www.bibsonomy.org/bibtex/2073f558b682ff264de2af731da8a3a3a/sdo},
booktitle = {The 10th International Semantic Web Conference (ISWC)},
interhash = {4cb80cbd6980b69e6b85b403cd548b91},
intrahash = {073f558b682ff264de2af731da8a3a3a},
keywords = {},
timestamp = {2012-02-29T10:50:09.000+0100},
title = {Semantic Smoothing for Twitter Sentiment Analysis},
year = 2011
}