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SNES: Social-Network-Oriented Public Opinion Monitoring Platform Based on ElasticSearch 被引量:1
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作者 Chuiju You Dongjie Zhu +5 位作者 Yundong Sun Anshan Ye Gangshan Wu Ning Cao Jinming Qiu Helen Min Zhou 《Computers, Materials & Continua》 SCIE EI 2019年第9期1271-1283,共13页
With the rapid development of social network,public opinion monitoring based on social networks is becoming more and more important.Many platforms have achieved some success in public opinion monitoring.However,these ... With the rapid development of social network,public opinion monitoring based on social networks is becoming more and more important.Many platforms have achieved some success in public opinion monitoring.However,these platforms cannot perform well in scalability,fault tolerance,and real-time performance.In this paper,we propose a novel social-network-oriented public opinion monitoring platform based on ElasticSearch(SNES).Firstly,SNES integrates the module of distributed crawler cluster,which provides real-time social media data access.Secondly,SNES integrates ElasticSearch which can store and retrieve massive unstructured data in near real time.Finally,we design subscription module based on Apache Kafka to connect the modules of the platform together in the form of message push and consumption,improving message throughput and the ability of dynamic horizontal scaling.A great number of empirical experiments prove that the platform can adapt well to the social network with highly real-time data and has good performance in public opinion monitoring. 展开更多
关键词 Social network public opinion monitoring elasticsearch scrapy-redis
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COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining 被引量:5
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作者 Yixian Zhang Jieren Cheng +6 位作者 Yifan Yang Haocheng Li Xinyi Zheng Xi Chen Boyi Liu Tenglong Ren Naixue Xiong 《Computers, Materials & Continua》 SCIE EI 2020年第9期1415-1434,共20页
With the spread and development of new epidemics,it is of great reference value to identify the changing trends of epidemics in public emotions.We designed and implemented the COVID-19 public opinion monitoring system... With the spread and development of new epidemics,it is of great reference value to identify the changing trends of epidemics in public emotions.We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining.A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed.Establish a“Scrapy-Redis-Bloomfilter”distributed crawler framework to collect data.The system can judge the positive and negative emotions of the reviewer based on the comments,and can also reflect the depth of the seven emotions such as Hopeful,Happy,and Depressed.Finally,we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model.The results show that our model has better generalization ability and smaller discriminant error.We designed a large data visualization screen,which can clearly show the trend of public emotions,the proportion of various emotion categories,keywords,hot topics,etc.,and fully and intuitively reflect the development of public opinion. 展开更多
关键词 COVID-19 public opinion monitoring data mining Chinese sentiment analysis data visualization
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