{"title":"用w -熵法衡量社会网络成员的影响力","authors":"Weigang Li, Jianya Zheng, Guiqiu Liu","doi":"10.1504/IJWET.2013.059105","DOIUrl":null,"url":null,"abstract":"With the rapid advance of the social media, the challenge is to develop new techniques and standards to measure the influence of people or brands in the online social networks. Each website has its way of ranking the display of the most influential members of its virtual society. However, most of the current measurement methods are incomplete and one-dimensional. This paper presents a new measurement model, W-entropy, which has been developed based on information theory to study the influence of individuals based on different social networks. The model was tested using data from Facebook, Twitter, YouTube, and Google search. The proposed model can be extended to other platforms. To evaluate the effectiveness, the developed method was compared with Famecount ranking using the same data with different weight distributions. The result shows that W-entropy method is suitable for index ranking to reflect uneven information distribution across various social networks.","PeriodicalId":396746,"journal":{"name":"Int. J. Web Eng. Technol.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"W-entropy method to measure the influence of the members from social networks\",\"authors\":\"Weigang Li, Jianya Zheng, Guiqiu Liu\",\"doi\":\"10.1504/IJWET.2013.059105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid advance of the social media, the challenge is to develop new techniques and standards to measure the influence of people or brands in the online social networks. Each website has its way of ranking the display of the most influential members of its virtual society. However, most of the current measurement methods are incomplete and one-dimensional. This paper presents a new measurement model, W-entropy, which has been developed based on information theory to study the influence of individuals based on different social networks. The model was tested using data from Facebook, Twitter, YouTube, and Google search. The proposed model can be extended to other platforms. To evaluate the effectiveness, the developed method was compared with Famecount ranking using the same data with different weight distributions. The result shows that W-entropy method is suitable for index ranking to reflect uneven information distribution across various social networks.\",\"PeriodicalId\":396746,\"journal\":{\"name\":\"Int. J. Web Eng. Technol.\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Web Eng. Technol.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJWET.2013.059105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Web Eng. Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJWET.2013.059105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
W-entropy method to measure the influence of the members from social networks
With the rapid advance of the social media, the challenge is to develop new techniques and standards to measure the influence of people or brands in the online social networks. Each website has its way of ranking the display of the most influential members of its virtual society. However, most of the current measurement methods are incomplete and one-dimensional. This paper presents a new measurement model, W-entropy, which has been developed based on information theory to study the influence of individuals based on different social networks. The model was tested using data from Facebook, Twitter, YouTube, and Google search. The proposed model can be extended to other platforms. To evaluate the effectiveness, the developed method was compared with Famecount ranking using the same data with different weight distributions. The result shows that W-entropy method is suitable for index ranking to reflect uneven information distribution across various social networks.