校园网网络情感分析

Jiao Wu, Weihua Gao, Bin Zhang, Y. Hu, Jinsong Liu
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引用次数: 9

摘要

用户对网络主题的评论是特别有用的信息。这些评论通常涉及积极、消极或混合情绪等情绪或观点,这些情绪或观点会影响其他用户的行为、心理和认知活动。传统的网络情感分析系统无法满足实时需求。在线网站情感分析系统的功能包括校园网流量采集、实时情感分析和离线网络话题情感分析。在线Web情感分析系统由前端监控节点、蜘蛛节点、控制节点、后端分析节点和数据仓库节点组成。实验结果表明,相同的主观词通过基本情感率(BSR)、校园用户率(CUR)、网络话题率(ITR)和人工影响率(MIR)可以达到不同的综合情感率(ISR)值。利用在线网络情感分析系统,可以即时发现校园网络上的网络话题情感。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Web Sentiment Analysis on Campus Network
The user review on a web topic is particular useful information. These reviews usually concern such sentiment or opinions as positive, negative or mixed mood which will affect other users' behaviors, psychological and cognitive activities. Classical web sentiment analysis system could not reach the real-time demand. The functions of online web sentiment analysis system are campus network net flow collection, real-time sentiment analysis and off-line Sentiment analysis on internet topic. Online Web Sentiment Analysis System is composed of Front-Monitor Node, Spider Node, Controller Node, Back-Analysis Node, and Data Warehouse Node. Experimental results show that the same subjective words can reach the different Integrated Sentiment Rate (ISR) value by Basic Sentiment Rate (BSR), Campus User Rate (CUR), Internet Topic Rate (ITR) and Manual Influence Rate (MIR). Using the online web sentiment analysis system, the internet topic sentiment on campus network can be discovered immediately.
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