{"title":"基于机器学习技术的社交媒体健康信息传播评价","authors":"Xiaoqing Lian, Cang Liang, Jing Li","doi":"10.1002/itl2.461","DOIUrl":null,"url":null,"abstract":"<p>Social media is an important channel for information dissemination in today's society. All kinds of enterprises, political organization, social organizations, etc. release all kinds of information through social media. This article conducted research and analysis on information on social media and effectively managed it. Machine learning methods can effectively solve the problem of analyzing health information (HI) in social media, thereby improving analysis efficiency and accuracy. This article explored the dissemination of social media HI based on machine learning technology, elaborated on the analysis and research of social media HI dissemination, discussed the importance of social media HI for the audience, and analyzed the empowerment of machine learning in HI dissemination. Through analysis and investigation, the new social media HI dissemination has increased by 0.09% compared with the traditional social media HI dissemination pseudoscience information identification; audience involvement has increased by 0.08; audience professionalism has increased by 0.2. Introducing machine learning into the field of HI content dissemination can help achieve customized production and crowdsourcing of content, from concept to reality, and from theory to practice, and thus trigger a new content revolution, shining new youth and vitality into HI dissemination.</p>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"7 6","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation on social media health information communication based on machine learning technology\",\"authors\":\"Xiaoqing Lian, Cang Liang, Jing Li\",\"doi\":\"10.1002/itl2.461\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Social media is an important channel for information dissemination in today's society. All kinds of enterprises, political organization, social organizations, etc. release all kinds of information through social media. This article conducted research and analysis on information on social media and effectively managed it. Machine learning methods can effectively solve the problem of analyzing health information (HI) in social media, thereby improving analysis efficiency and accuracy. This article explored the dissemination of social media HI based on machine learning technology, elaborated on the analysis and research of social media HI dissemination, discussed the importance of social media HI for the audience, and analyzed the empowerment of machine learning in HI dissemination. Through analysis and investigation, the new social media HI dissemination has increased by 0.09% compared with the traditional social media HI dissemination pseudoscience information identification; audience involvement has increased by 0.08; audience professionalism has increased by 0.2. Introducing machine learning into the field of HI content dissemination can help achieve customized production and crowdsourcing of content, from concept to reality, and from theory to practice, and thus trigger a new content revolution, shining new youth and vitality into HI dissemination.</p>\",\"PeriodicalId\":100725,\"journal\":{\"name\":\"Internet Technology Letters\",\"volume\":\"7 6\",\"pages\":\"\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2023-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet Technology Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/itl2.461\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet Technology Letters","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/itl2.461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Evaluation on social media health information communication based on machine learning technology
Social media is an important channel for information dissemination in today's society. All kinds of enterprises, political organization, social organizations, etc. release all kinds of information through social media. This article conducted research and analysis on information on social media and effectively managed it. Machine learning methods can effectively solve the problem of analyzing health information (HI) in social media, thereby improving analysis efficiency and accuracy. This article explored the dissemination of social media HI based on machine learning technology, elaborated on the analysis and research of social media HI dissemination, discussed the importance of social media HI for the audience, and analyzed the empowerment of machine learning in HI dissemination. Through analysis and investigation, the new social media HI dissemination has increased by 0.09% compared with the traditional social media HI dissemination pseudoscience information identification; audience involvement has increased by 0.08; audience professionalism has increased by 0.2. Introducing machine learning into the field of HI content dissemination can help achieve customized production and crowdsourcing of content, from concept to reality, and from theory to practice, and thus trigger a new content revolution, shining new youth and vitality into HI dissemination.