东篱科研大数据发现系统（DRDS）

位置：成果数据库 > 期刊 > 期刊详情页

Design and Implementation of Weibo Sentiment Analysis Based on LDA and Dependency Parsing

ISSN号：1673-5447
期刊名称：《中国通信：英文版》
时间：0
分类：TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术] TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
作者机构：[1]Computer School of Wuhan University, Wuhan University, Wuhan 430079, China, [2]The Key Laboratory of Aerospace Information Security and Trust Computing, Ministry of Education, Wuhan 430072, China, [3]Department of Information Security, Navy University of Engineering, Wuhan 430033, China, [4]Unit Number of 92941, PLA, Huludao, Liaoning Province 125000, China
相关基金：supported by National Key Basic Research Program of China （No.2014CB340600）; partially supported by National Natural Science Foundation of China （Grant Nos.61332019,61672531）; partially supported by National Social Science Foundation of China （Grant No.14GJ003-152）

作者： Yonggan Li[1,2], Xueguang Zhou[3], Yan Sun[4], Huanguo Zhang[1,2]

关键词：情感表达, 句法分析, LDA, 设计, 网络空间安全, 内容安全, 合并算法, 吉布斯抽样, information security, information content security, sentiment analysis, dependency parsing, emotion tendency classification, emotion expression extraction

中文摘要：

Information content security is a branch of cyberspace security. How to effectively manage and use Weibo comment information has become a research focus in the field of information content security. Three main tasks involved are emotion sentence identification and classification,emotion tendency classification,and emotion expression extraction. Combining with the latent Dirichlet allocation(LDA) model,a Gibbs sampling implementation for inference of our algorithm is presented,and can be used to categorize emotion tendency automatically with the computer. In accordance with the lower ratio of recall for emotion expression extraction in Weibo,use dependency parsing,divided into two categories with subject and object,summarized six kinds of dependency models from evaluating objects and emotion words,and proposed that a merge algorithm for evaluating objects can be accurately evaluated by participating in a public bakeoff and in the shared tasks among the best methods in the sub-task of emotion expression extraction,indicating the value of our method as not only innovative but practical.

英文摘要：

Information content security is a branch of cyberspace security. How to effectively manage and use Weibo comment information has become a research focus in the field of information content security. Three main tasks involved are emotion sentence identification and classification,emotion tendency classification,and emotion expression extraction. Combining with the latent Dirichlet allocation（LDA） model,a Gibbs sampling implementation for inference of our algorithm is presented,and can be used to categorize emotion tendency automatically with the computer. In accordance with the lower ratio of recall for emotion expression extraction in Weibo,use dependency parsing,divided into two categories with subject and object,summarized six kinds of dependency models from evaluating objects and emotion words,and proposed that a merge algorithm for evaluating objects can be accurately evaluated by participating in a public bakeoff and in the shared tasks among the best methods in the sub-task of emotion expression extraction,indicating the value of our method as not only innovative but practical.

同期刊论文项目