Jiao Wu, Weihua Gao, Bin Zhang, Y. Hu, Jinsong Liu
{"title":"校园网网络情感分析","authors":"Jiao Wu, Weihua Gao, Bin Zhang, Y. Hu, Jinsong Liu","doi":"10.1109/ISCID.2011.197","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":224504,"journal":{"name":"2011 Fourth International Symposium on Computational Intelligence and Design","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Online Web Sentiment Analysis on Campus Network\",\"authors\":\"Jiao Wu, Weihua Gao, Bin Zhang, Y. Hu, Jinsong Liu\",\"doi\":\"10.1109/ISCID.2011.197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":224504,\"journal\":{\"name\":\"2011 Fourth International Symposium on Computational Intelligence and Design\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Fourth International Symposium on Computational Intelligence and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCID.2011.197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Fourth International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2011.197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.