Cumulative Effect in Information Diffusion: Empirical Study on a Microblogging Network
Cumulative effect in social contagion underlies many studies on the spread of innovation, behavior, and influence. However, few large-scale empirical studies are conducted to validate the existence of cumulative effect in information diffusion on social networks. In this paper, using the population-...
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| Published in | PloS one Vol. 8; no. 10; p. e76027 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
01.10.2013
Public Library of Science (PLoS) |
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| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0076027 |
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| Abstract | Cumulative effect in social contagion underlies many studies on the spread of innovation, behavior, and influence. However, few large-scale empirical studies are conducted to validate the existence of cumulative effect in information diffusion on social networks. In this paper, using the population-scale dataset from the largest Chinese microblogging website, we conduct a comprehensive study on the cumulative effect in information diffusion. We base our study on the diffusion network of message, where nodes are the involved users and links characterize forwarding relationship among them. We find that multiple exposures to the same message indeed increase the possibility of forwarding it. However, additional exposures cannot further improve the chance of forwarding when the number of exposures crosses its peak at two. This finding questions the cumulative effect hypothesis in information diffusion. Furthermore, to clarify the forwarding preference among users, we investigate both structural motif in the diffusion network and temporal pattern in information diffusion process. Findings provide some insights for understanding the variation of message popularity and explain the characteristics of diffusion network. |
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| AbstractList | Cumulative effect in social contagion underlies many studies on the spread of innovation, behavior, and influence. However, few large-scale empirical studies are conducted to validate the existence of cumulative effect in information diffusion on social networks. In this paper, using the population-scale dataset from the largest Chinese microblogging website, we conduct a comprehensive study on the cumulative effect in information diffusion. We base our study on the diffusion network of message, where nodes are the involved users and links characterize forwarding relationship among them. We find that multiple exposures to the same message indeed increase the possibility of forwarding it. However, additional exposures cannot further improve the chance of forwarding when the number of exposures crosses its peak at two. This finding questions the cumulative effect hypothesis in information diffusion. Furthermore, to clarify the forwarding preference among users, we investigate both structural motif in the diffusion network and temporal pattern in information diffusion process. Findings provide some insights for understanding the variation of message popularity and explain the characteristics of diffusion network. Cumulative effect in social contagion underlies many studies on the spread of innovation, behavior, and influence. However, few large-scale empirical studies are conducted to validate the existence of cumulative effect in information diffusion on social networks. In this paper, using the population-scale dataset from the largest Chinese microblogging website, we conduct a comprehensive study on the cumulative effect in information diffusion. We base our study on the diffusion network of message, where nodes are the involved users and links characterize forwarding relationship among them. We find that multiple exposures to the same message indeed increase the possibility of forwarding it. However, additional exposures cannot further improve the chance of forwarding when the number of exposures crosses its peak at two. This finding questions the cumulative effect hypothesis in information diffusion. Furthermore, to clarify the forwarding preference among users, we investigate both structural motif in the diffusion network and temporal pattern in information diffusion process. Findings provide some insights for understanding the variation of message popularity and explain the characteristics of diffusion network.Cumulative effect in social contagion underlies many studies on the spread of innovation, behavior, and influence. However, few large-scale empirical studies are conducted to validate the existence of cumulative effect in information diffusion on social networks. In this paper, using the population-scale dataset from the largest Chinese microblogging website, we conduct a comprehensive study on the cumulative effect in information diffusion. We base our study on the diffusion network of message, where nodes are the involved users and links characterize forwarding relationship among them. We find that multiple exposures to the same message indeed increase the possibility of forwarding it. However, additional exposures cannot further improve the chance of forwarding when the number of exposures crosses its peak at two. This finding questions the cumulative effect hypothesis in information diffusion. Furthermore, to clarify the forwarding preference among users, we investigate both structural motif in the diffusion network and temporal pattern in information diffusion process. Findings provide some insights for understanding the variation of message popularity and explain the characteristics of diffusion network. |
| Audience | Academic |
| Author | Chen, Wei Bao, Peng Shen, Hua-Wei Cheng, Xue-Qi |
| AuthorAffiliation | Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China University of Zaragoza, Spain |
| AuthorAffiliation_xml | – name: University of Zaragoza, Spain – name: Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China |
| Author_xml | – sequence: 1 givenname: Peng surname: Bao fullname: Bao, Peng – sequence: 2 givenname: Hua-Wei surname: Shen fullname: Shen, Hua-Wei – sequence: 3 givenname: Wei surname: Chen fullname: Chen, Wei – sequence: 4 givenname: Xue-Qi surname: Cheng fullname: Cheng, Xue-Qi |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24098422$$D View this record in MEDLINE/PubMed |
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| Copyright | COPYRIGHT 2013 Public Library of Science 2013 Bao et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2013 Bao et al 2013 Bao et al |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: PB HWS WC XQC. Performed the experiments: PB HWS WC. Analyzed the data: PB. Contributed reagents/materials/analysis tools: PB HWS WC. Wrote the paper: PB HWS WC XQC. |
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| SubjectTerms | Analysis Blogging Data mining Diffusion Diffusion effects Exposure Humans Information Dissemination Information processing Innovations International conferences Internet Mechanics Microblogs Models, Statistical Neural Networks (Computer) Neurosciences Science Social behavior Social Media Social networks Social organization Studies World Wide Web |
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| Title | Cumulative Effect in Information Diffusion: Empirical Study on a Microblogging Network |
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