Sentiment Analysis on Smoking in Social Networks

被引：7

作者：

Sofean, Mustafa ^{[1
]}

Smith, Matthew ^{[1
]}

机构：

[1] Leibniz Univ Hannover, Distributed Comp & Secur Grp, Hannover, Germany

来源：

MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2 | 2013年 / 192卷

关键词：

Twitter; Opinion Mining; Data Mining;

D O I：

10.3233/978-1-61499-289-9-1118

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

Online social networks play a vital role in daily life to share the opinions or behaviors on different topics. The data of social networks can be used to understand health-related behaviors. In this work, we used Twitter status updates to survey of smoking behaviors among the users. We introduce approach to classify the sentiment of smoke-related tweets into positive and negative tweets. The classifier is based on the Support Vector Machines (SVMs) and can achieve high accuracy up to 86%.

引用

页码：1118 / 1118

页数：1