How events determine spreading patterns: information transmission via internal and external influences on social networks
Recently, information transmission models motivated by the classical epidemic propagation, have been applied to a wide-range of social systems, generally assume that information mainly transmits among individuals via peer-to-peer interactions on social networks. In this paper, we consider one more a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2015-01-01
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| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/17/11/113045 |
| _version_ | 1797751028327645184 |
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| author | Chuang Liu Xiu-Xiu Zhan Zi-Ke Zhang Gui-Quan Sun Pak Ming Hui |
| author_facet | Chuang Liu Xiu-Xiu Zhan Zi-Ke Zhang Gui-Quan Sun Pak Ming Hui |
| author_sort | Chuang Liu |
| collection | DOAJ |
| description | Recently, information transmission models motivated by the classical epidemic propagation, have been applied to a wide-range of social systems, generally assume that information mainly transmits among individuals via peer-to-peer interactions on social networks. In this paper, we consider one more approach for users to get information: the out-of-social-network influence. Empirical analyzes of eight typical events’ diffusion on a very large micro-blogging system, Sina Weibo , show that the external influence has significant impact on information spreading along with social activities. In addition, we propose a theoretical model to interpret the spreading process via both internal and external channels, considering three essential properties: (i) memory effect; (ii) role of spreaders; and (iii) non-redundancy of contacts. Experimental and mathematical results indicate that the information indeed spreads much quicker and broader with mutual effects of the internal and external influences. More importantly, the present model reveals that the event characteristic would highly determine the essential spreading patterns once the network structure is established. The results may shed some light on the in-depth understanding of the underlying dynamics of information transmission on real social networks. |
| first_indexed | 2024-03-12T16:42:26Z |
| format | Article |
| id | doaj.art-5cdf900e753d4c90b3898ce858cece22 |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:42:26Z |
| publishDate | 2015-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-5cdf900e753d4c90b3898ce858cece222023-08-08T14:23:45ZengIOP PublishingNew Journal of Physics1367-26302015-01-01171111304510.1088/1367-2630/17/11/113045How events determine spreading patterns: information transmission via internal and external influences on social networksChuang Liu0Xiu-Xiu Zhan1Zi-Ke Zhang2Gui-Quan Sun3Pak Ming Hui4Alibaba Research Center for Complexity Sciences, Hangzhou Normal University , Hangzhou 311121, People’s Republic of ChinaAlibaba Research Center for Complexity Sciences, Hangzhou Normal University , Hangzhou 311121, People’s Republic of China; Department of Mathematics, North University of China , Taiyuan 030051, People’s Republic of ChinaAlibaba Research Center for Complexity Sciences, Hangzhou Normal University , Hangzhou 311121, People’s Republic of China; Alibaba Research Institute , Hangzhou, 311121, People’s Republic of ChinaDepartment of Mathematics, North University of China , Taiyuan 030051, People’s Republic of ChinaDepartment of Physics, The Chinese University of Hong Kong , Shatin, New Territories, Hong Kong, People’s Republic of ChinaRecently, information transmission models motivated by the classical epidemic propagation, have been applied to a wide-range of social systems, generally assume that information mainly transmits among individuals via peer-to-peer interactions on social networks. In this paper, we consider one more approach for users to get information: the out-of-social-network influence. Empirical analyzes of eight typical events’ diffusion on a very large micro-blogging system, Sina Weibo , show that the external influence has significant impact on information spreading along with social activities. In addition, we propose a theoretical model to interpret the spreading process via both internal and external channels, considering three essential properties: (i) memory effect; (ii) role of spreaders; and (iii) non-redundancy of contacts. Experimental and mathematical results indicate that the information indeed spreads much quicker and broader with mutual effects of the internal and external influences. More importantly, the present model reveals that the event characteristic would highly determine the essential spreading patterns once the network structure is established. The results may shed some light on the in-depth understanding of the underlying dynamics of information transmission on real social networks.https://doi.org/10.1088/1367-2630/17/11/113045epidemic spreadingsocial networksinformation spreadingcomplex networks |
| spellingShingle | Chuang Liu Xiu-Xiu Zhan Zi-Ke Zhang Gui-Quan Sun Pak Ming Hui How events determine spreading patterns: information transmission via internal and external influences on social networks New Journal of Physics epidemic spreading social networks information spreading complex networks |
| title | How events determine spreading patterns: information transmission via internal and external influences on social networks |
| title_full | How events determine spreading patterns: information transmission via internal and external influences on social networks |
| title_fullStr | How events determine spreading patterns: information transmission via internal and external influences on social networks |
| title_full_unstemmed | How events determine spreading patterns: information transmission via internal and external influences on social networks |
| title_short | How events determine spreading patterns: information transmission via internal and external influences on social networks |
| title_sort | how events determine spreading patterns information transmission via internal and external influences on social networks |
| topic | epidemic spreading social networks information spreading complex networks |
| url | https://doi.org/10.1088/1367-2630/17/11/113045 |
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