{"title":"Twitter和电子健康:Twitter上可视化癌症网络的案例研究","authors":"D. Murthy, Alexander Gross, Scott A. Longwell","doi":"10.1109/I-SOCIETY18435.2011.5978519","DOIUrl":null,"url":null,"abstract":"This paper seeks to understand health-related social networks on social media websites. The paper explores fundamental questions about social networks formed in the prominent social media website Twitter and demonstrates innovative new methods to conduct applied research in the health sciences using social media networks. The paper aims to address fundamental questions about health-related social networks in emergent social media regarding information flow and network structure. The paper uses a dataset built from Twitter data using a well-known American oncologist as a ‘seed’ and crawled the Twitter network three degrees out to form a total network of over 30 million nodes","PeriodicalId":158246,"journal":{"name":"International Conference on Information Society (i-Society 2011)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Twitter and e-health: A case study of visualizing cancer networks on Twitter\",\"authors\":\"D. Murthy, Alexander Gross, Scott A. Longwell\",\"doi\":\"10.1109/I-SOCIETY18435.2011.5978519\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper seeks to understand health-related social networks on social media websites. The paper explores fundamental questions about social networks formed in the prominent social media website Twitter and demonstrates innovative new methods to conduct applied research in the health sciences using social media networks. The paper aims to address fundamental questions about health-related social networks in emergent social media regarding information flow and network structure. The paper uses a dataset built from Twitter data using a well-known American oncologist as a ‘seed’ and crawled the Twitter network three degrees out to form a total network of over 30 million nodes\",\"PeriodicalId\":158246,\"journal\":{\"name\":\"International Conference on Information Society (i-Society 2011)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Information Society (i-Society 2011)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I-SOCIETY18435.2011.5978519\",\"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 Information Society (i-Society 2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SOCIETY18435.2011.5978519","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Twitter and e-health: A case study of visualizing cancer networks on Twitter
This paper seeks to understand health-related social networks on social media websites. The paper explores fundamental questions about social networks formed in the prominent social media website Twitter and demonstrates innovative new methods to conduct applied research in the health sciences using social media networks. The paper aims to address fundamental questions about health-related social networks in emergent social media regarding information flow and network structure. The paper uses a dataset built from Twitter data using a well-known American oncologist as a ‘seed’ and crawled the Twitter network three degrees out to form a total network of over 30 million nodes