Virality and susceptibility in information diffusions
Viral diffusion allows a piece of information to widely and quickly spread within the network of users through word-ofmouth. In this paper, we study the problem of modeling both item and user factors that contribute to viral diffusion in Twitter network. We identify three behaviorial factors, namely...
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sg-smu-ink.sis_research-25452018-07-13T02:51:51Z Virality and susceptibility in information diffusions HOANG, Tuan-Anh LIM, Ee Peng Viral diffusion allows a piece of information to widely and quickly spread within the network of users through word-ofmouth. In this paper, we study the problem of modeling both item and user factors that contribute to viral diffusion in Twitter network. We identify three behaviorial factors, namely user virality, user susceptibility and item virality, that contribute to viral diffusion. Instead of modeling these factors independently as done in previous research, we propose a model that measures all the factors simultaneously considering their mutual dependencies. The model has been evaluated on both synthetic and real datasets. The experiments show that our model outperforms the existing ones for synthetic data with ground truth labels. Our model also performs well for predicting the hashtags that have higher retweet likelihood. We finally present case examples that illustrate how the models differ from one another. 2012-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1546 https://ink.library.smu.edu.sg/context/sis_research/article/2545/viewcontent/C11___Virality_and_Susceptibility_in_Information_Diffusions__ICWSM12___Jun12.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Viral diffusion Diffusion related factors Twitter network Databases and Information Systems Numerical Analysis and Scientific Computing |
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Viral diffusion Diffusion related factors Twitter network Databases and Information Systems Numerical Analysis and Scientific Computing HOANG, Tuan-Anh LIM, Ee Peng Virality and susceptibility in information diffusions |
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Viral diffusion allows a piece of information to widely and quickly spread within the network of users through word-ofmouth. In this paper, we study the problem of modeling both item and user factors that contribute to viral diffusion in Twitter network. We identify three behaviorial factors, namely user virality, user susceptibility and item virality, that contribute to viral diffusion. Instead of modeling these factors independently as done in previous research, we propose a model that measures all the factors simultaneously considering their mutual dependencies. The model has been evaluated on both synthetic and real datasets. The experiments show that our model outperforms the existing ones for synthetic data with ground truth labels. Our model also performs well for predicting the hashtags that have higher retweet likelihood. We finally present case examples that illustrate how the models differ from one another. |
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HOANG, Tuan-Anh LIM, Ee Peng |
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HOANG, Tuan-Anh LIM, Ee Peng |
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HOANG, Tuan-Anh |
title |
Virality and susceptibility in information diffusions |
title_short |
Virality and susceptibility in information diffusions |
title_full |
Virality and susceptibility in information diffusions |
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Virality and susceptibility in information diffusions |
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Virality and susceptibility in information diffusions |
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virality and susceptibility in information diffusions |
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Institutional Knowledge at Singapore Management University |
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2012 |
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https://ink.library.smu.edu.sg/sis_research/1546 https://ink.library.smu.edu.sg/context/sis_research/article/2545/viewcontent/C11___Virality_and_Susceptibility_in_Information_Diffusions__ICWSM12___Jun12.pdf |
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