Tracking virality and susceptibility in social media
In social media, the magnitude of information propagation hinges on the virality and susceptibility of users spreading and receiving the information respectively, as well as the virality of information items. These users' and items' behavioral factors evolve dynamically at the same time in...
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sg-smu-ink.sis_research-44592017-03-31T06:24:28Z Tracking virality and susceptibility in social media HOANG, Tuan Anh LIM, Ee-Peng In social media, the magnitude of information propagation hinges on the virality and susceptibility of users spreading and receiving the information respectively, as well as the virality of information items. These users' and items' behavioral factors evolve dynamically at the same time interacting with one another. Previous works however measure the factors statically and independently in a restricted case: each user has only a single adoption on each item, and/or users' exposure to items are observable. In this work, we investigate the inter-relationship among the factors and users' multiple adoptions on items to propose both new static and temporal models for measuring the factors without requiring user - item exposure. These models are designed to cope with even more realistic propagation scenarios where an item may be propagated many times from the same user(s) to the same other user(s). We further propose an incremental model for measuring the factors in large data streams. We evaluated the proposed models and existing models through extensive experiments on a large Twitter dataset covering information propagation in one month. The experiments show that our proposed models can effectively mine the behavioral factors and outperform the existing ones in a propagation prediction task. The incremental model is shown more than 10 times faster than the temporal model, while still obtains very similar results. 2016-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3458 info:doi/10.1145/2983323.2983800 https://ink.library.smu.edu.sg/context/sis_research/article/4459/viewcontent/173___Tracking_Virality_and_Susceptibility_in_Social_Media__CIKM2016_.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 Virality Susceptibility User behavior Information propagation Computer Sciences Databases and Information Systems Social Media |
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Virality Susceptibility User behavior Information propagation Computer Sciences Databases and Information Systems Social Media HOANG, Tuan Anh LIM, Ee-Peng Tracking virality and susceptibility in social media |
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In social media, the magnitude of information propagation hinges on the virality and susceptibility of users spreading and receiving the information respectively, as well as the virality of information items. These users' and items' behavioral factors evolve dynamically at the same time interacting with one another. Previous works however measure the factors statically and independently in a restricted case: each user has only a single adoption on each item, and/or users' exposure to items are observable. In this work, we investigate the inter-relationship among the factors and users' multiple adoptions on items to propose both new static and temporal models for measuring the factors without requiring user - item exposure. These models are designed to cope with even more realistic propagation scenarios where an item may be propagated many times from the same user(s) to the same other user(s). We further propose an incremental model for measuring the factors in large data streams. We evaluated the proposed models and existing models through extensive experiments on a large Twitter dataset covering information propagation in one month. The experiments show that our proposed models can effectively mine the behavioral factors and outperform the existing ones in a propagation prediction task. The incremental model is shown more than 10 times faster than the temporal model, while still obtains very similar results. |
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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 |
Tracking virality and susceptibility in social media |
title_short |
Tracking virality and susceptibility in social media |
title_full |
Tracking virality and susceptibility in social media |
title_fullStr |
Tracking virality and susceptibility in social media |
title_full_unstemmed |
Tracking virality and susceptibility in social media |
title_sort |
tracking virality and susceptibility in social media |
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Institutional Knowledge at Singapore Management University |
publishDate |
2016 |
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https://ink.library.smu.edu.sg/sis_research/3458 https://ink.library.smu.edu.sg/context/sis_research/article/4459/viewcontent/173___Tracking_Virality_and_Susceptibility_in_Social_Media__CIKM2016_.pdf |
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