Xiangfeng Luo, Lei Zhang, Yawen Yi, Ruirong Xue, D. Jiang
{"title":"基于用户重要性计算的关键用户发现模型","authors":"Xiangfeng Luo, Lei Zhang, Yawen Yi, Ruirong Xue, D. Jiang","doi":"10.1504/ijcse.2020.10027436","DOIUrl":null,"url":null,"abstract":"Recently, more and more users publish their views on events in social media. Identifying influential users in social media can help to analyse the impact of hot events or enterprise products in the real world. The existing mainstream methods are based on attribute analysis or network analysis. But attribute-based methods only select relatively simple characteristics without examining the event targeted properties; the network-based methods only use the user behaviour relation or the content association relation to build a network without considering the user attributes. Therefore, they cannot effectively calculate the user importance. This paper proposes a multi-angle user importance calculation method with event-specificity. In our method, the overall importance of a user is measured by taking the four levels within the user layer, the fan layer, the microblog layer, and the event layer into account. Experimental results show that our method can effectively calculate the importance of users.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The key user discovery model based on user importance calculation\",\"authors\":\"Xiangfeng Luo, Lei Zhang, Yawen Yi, Ruirong Xue, D. Jiang\",\"doi\":\"10.1504/ijcse.2020.10027436\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, more and more users publish their views on events in social media. Identifying influential users in social media can help to analyse the impact of hot events or enterprise products in the real world. The existing mainstream methods are based on attribute analysis or network analysis. But attribute-based methods only select relatively simple characteristics without examining the event targeted properties; the network-based methods only use the user behaviour relation or the content association relation to build a network without considering the user attributes. Therefore, they cannot effectively calculate the user importance. This paper proposes a multi-angle user importance calculation method with event-specificity. In our method, the overall importance of a user is measured by taking the four levels within the user layer, the fan layer, the microblog layer, and the event layer into account. Experimental results show that our method can effectively calculate the importance of users.\",\"PeriodicalId\":340410,\"journal\":{\"name\":\"Int. J. Comput. Sci. Eng.\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Comput. Sci. Eng.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijcse.2020.10027436\",\"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. Comput. Sci. Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijcse.2020.10027436","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The key user discovery model based on user importance calculation
Recently, more and more users publish their views on events in social media. Identifying influential users in social media can help to analyse the impact of hot events or enterprise products in the real world. The existing mainstream methods are based on attribute analysis or network analysis. But attribute-based methods only select relatively simple characteristics without examining the event targeted properties; the network-based methods only use the user behaviour relation or the content association relation to build a network without considering the user attributes. Therefore, they cannot effectively calculate the user importance. This paper proposes a multi-angle user importance calculation method with event-specificity. In our method, the overall importance of a user is measured by taking the four levels within the user layer, the fan layer, the microblog layer, and the event layer into account. Experimental results show that our method can effectively calculate the importance of users.