V. Karyukin, A. Zhumabekova, Sandugash Yessenzhanova
{"title":"分析社交媒体的机器学习和神经网络方法","authors":"V. Karyukin, A. Zhumabekova, Sandugash Yessenzhanova","doi":"10.1145/3410352.3410739","DOIUrl":null,"url":null,"abstract":"The rapid development of the Internet has led to a significant increase in the number of news sites and social networks that describe various events in the world and society. People actively share their opinions about various events in the world. Manually tracking and analyzing such a volume of information is not possible. So, in this way, the use of algorithms for automatic analysis of texts and user comments is an important feature. Published articles and user comments in most cases are of a certain emotional aspect. This article analyzes texts and user comments of Kazakhstan media space. Sentiment classification is done using machine learning algorithms and convolutional and recurrent neural networks (CNN and RNN). A comparative review of the obtained results was performed after the classification.","PeriodicalId":178037,"journal":{"name":"Proceedings of the 6th International Conference on Engineering & MIS 2020","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Machine Learning And Neural Network Methodologies of Analyzing Social Media\",\"authors\":\"V. Karyukin, A. Zhumabekova, Sandugash Yessenzhanova\",\"doi\":\"10.1145/3410352.3410739\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid development of the Internet has led to a significant increase in the number of news sites and social networks that describe various events in the world and society. People actively share their opinions about various events in the world. Manually tracking and analyzing such a volume of information is not possible. So, in this way, the use of algorithms for automatic analysis of texts and user comments is an important feature. Published articles and user comments in most cases are of a certain emotional aspect. This article analyzes texts and user comments of Kazakhstan media space. Sentiment classification is done using machine learning algorithms and convolutional and recurrent neural networks (CNN and RNN). A comparative review of the obtained results was performed after the classification.\",\"PeriodicalId\":178037,\"journal\":{\"name\":\"Proceedings of the 6th International Conference on Engineering & MIS 2020\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th International Conference on Engineering & MIS 2020\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3410352.3410739\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Engineering & MIS 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3410352.3410739","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine Learning And Neural Network Methodologies of Analyzing Social Media
The rapid development of the Internet has led to a significant increase in the number of news sites and social networks that describe various events in the world and society. People actively share their opinions about various events in the world. Manually tracking and analyzing such a volume of information is not possible. So, in this way, the use of algorithms for automatic analysis of texts and user comments is an important feature. Published articles and user comments in most cases are of a certain emotional aspect. This article analyzes texts and user comments of Kazakhstan media space. Sentiment classification is done using machine learning algorithms and convolutional and recurrent neural networks (CNN and RNN). A comparative review of the obtained results was performed after the classification.