{"title":"在线论坛真实性:医疗保健领域的大数据分析","authors":"G. Zhan","doi":"10.1145/3318299.3318395","DOIUrl":null,"url":null,"abstract":"It is difficult to discern the authenticity online reviews, which is critical particularly in a setting of patient-doctor online forum. In this paper, a model on the detection of doctor quality has been developed and tested with online big data. In this study, a database with 31,646 online reviews was compiled. Text mining and word-cloud analysis results indicate that the model provides an effective solution to assess the quality of doctors registered in online forum, the quality of doctor-patient online interaction, and patients' overall perception. A guideline has been provided to evaluate doctor authenticity.","PeriodicalId":164987,"journal":{"name":"International Conference on Machine Learning and Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Online Forum Authenticity: Big Data Analytics in Healthcare\",\"authors\":\"G. Zhan\",\"doi\":\"10.1145/3318299.3318395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is difficult to discern the authenticity online reviews, which is critical particularly in a setting of patient-doctor online forum. In this paper, a model on the detection of doctor quality has been developed and tested with online big data. In this study, a database with 31,646 online reviews was compiled. Text mining and word-cloud analysis results indicate that the model provides an effective solution to assess the quality of doctors registered in online forum, the quality of doctor-patient online interaction, and patients' overall perception. A guideline has been provided to evaluate doctor authenticity.\",\"PeriodicalId\":164987,\"journal\":{\"name\":\"International Conference on Machine Learning and Computing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Machine Learning and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3318299.3318395\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Machine Learning and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3318299.3318395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Online Forum Authenticity: Big Data Analytics in Healthcare
It is difficult to discern the authenticity online reviews, which is critical particularly in a setting of patient-doctor online forum. In this paper, a model on the detection of doctor quality has been developed and tested with online big data. In this study, a database with 31,646 online reviews was compiled. Text mining and word-cloud analysis results indicate that the model provides an effective solution to assess the quality of doctors registered in online forum, the quality of doctor-patient online interaction, and patients' overall perception. A guideline has been provided to evaluate doctor authenticity.
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