Estimation of social network user's influence in a given area of expertise; Journal of Physics: Conference Series; Vol. 803 : Information Technologies in Business and Industry (ITBI2016)

Detalhes bibliográficos
Parent link:Journal of Physics: Conference Series
Vol. 803 : Information Technologies in Business and Industry (ITBI2016).— 2017.— [012089, 6 p.]
Autor Corporativo: Томский политехнический университет Институт кибернетики, ИК
Outros Autores: Luneva E. E. Elena Evgenievna, Zamyatina V. S., Banokin P. I. Pavel Ivanovich, Efremov A. A. Aleksandr Aleksandrovich
Resumo:Title screen
Nowadays social networks are frequently used to express personal opinion on a topic of interest. Some users' opinion has more informational influence than others do. These users are called influential users. There are services that allow evaluating how popular and influential users are; however, any information on evaluation methods is proprietary and represents know-how of such software services. Furthermore, most services could not provide extensive data on the influential users within the specified area of knowledge. This article proposes the method of evaluating a user influence index within a social network in a given area of expertise.
Idioma:inglês
Publicado em: 2017
Assuntos:
Acesso em linha:http://dx.doi.org/10.1088/1742-6596/803/1/012089
http://earchive.tpu.ru/handle/11683/38159
Formato: Recurso Eletrônico Capítulo de Livro
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654362

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330 |a Nowadays social networks are frequently used to express personal opinion on a topic of interest. Some users' opinion has more informational influence than others do. These users are called influential users. There are services that allow evaluating how popular and influential users are; however, any information on evaluation methods is proprietary and represents know-how of such software services. Furthermore, most services could not provide extensive data on the influential users within the specified area of knowledge. This article proposes the method of evaluating a user influence index within a social network in a given area of expertise. 
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