The role of different tie strength in disseminating different topics on a microblog

The study of information flow typically does not distinguish the choices of tie strength on which the information flows. All receivers of the information are assumed to have the same potential to pass on the information. Modifying the SEIZ (susceptible, exposed, infected, skeptic) model, we discover...

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Bibliographic Details
Main Authors: NATALI, Felicia, CARLEY, Kathleen M., ZHU, Feida, HUANG, Binxuan
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/sis_research/3927
https://ink.library.smu.edu.sg/context/sis_research/article/4929/viewcontent/p203_Natali__1_.pdf
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Institution: Singapore Management University
Language: English
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Summary:The study of information flow typically does not distinguish the choices of tie strength on which the information flows. All receivers of the information are assumed to have the same potential to pass on the information. Modifying the SEIZ (susceptible, exposed, infected, skeptic) model, we discover that people choose to retweet strong or weak ties based on the topic. We made two modifications in the model. In the first modification (Model I), we assume that the contact rates of agents in different compartment and the probability of an agent transitioning from one compartment to another are different for strong ties and weak ties. In the second modification (Model II), we assume that only the probability of transitioning is different for strong ties and weak ties. We discover that people do not discriminate strong ties and weak ties when retweeting controversial topic, perhaps because this topic can both be personal and breaking news. On the other hand, people discriminate strong ties and weak ties when retweeting non-controversial topic. They prefer to retweet strong ties when the topic is donation, and kids, and weak ties when the topic is news on hurricane and music. Meanwhile, SEIZ model and its modifications are found to be inadequate to model tweets on event promotion.